Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Multimedia over wireless ip networks:distortion estimation and applications.

2006/2007This thesis deals with multimedia communication over unreliable and resource constrained IP-based packet-switched networks. The focus is on estimating, evaluating and enhancing the quality of streaming media services with particular regard to video services. The original contributions of this study involve mainly the development of three video distortion estimation techniques and the successive definition of some application scenarios used to demonstrate the benefits obtained applying such algorithms. The material presented in this dissertation is the result of the studies performed within the Telecommunication Group of the Department of Electronic Engineering at the University of Trieste during the course of Doctorate in Information Engineering. In recent years multimedia communication over wired and wireless packet based networks is exploding. Applications such as BitTorrent, music file sharing, multimedia podcasting are the main source of all traffic on the Internet. Internet radio for example is now evolving into peer to peer television such as CoolStreaming. Moreover, web sites such as YouTube have made publishing videos on demand available to anyone owning a home video camera. Another challenge in the multimedia evolution is inside the house where videos are distributed over local WiFi networks to many end devices around the house. More in general we are assisting an all media over IP revolution, with radio, television, telephony and stored media all being delivered over IP wired and wireless networks. All the presented applications require an extreme high bandwidth and often a low delay especially for interactive applications. Unfortunately the Internet and the wireless networks provide only limited support for multimedia applications. Variations in network conditions can have considerable consequences for real-time multimedia applications and can lead to unsatisfactory user experience. In fact, multimedia applications are usually delay sensitive, bandwidth intense and loss tolerant applications. In order to overcame this limitations, efficient adaptation mechanism must be derived to bridge the application requirements with the transport medium characteristics. Several approaches have been proposed for the robust transmission of multimedia packets; they range from source coding solutions to the addition of redundancy with forward error correction and retransmissions. Additionally, other techniques are based on developing efficient QoS architectures at the network layer or at the data link layer where routers or specialized devices apply different forwarding behaviors to packets depending on the value of some field in the packet header. Using such network architecture, video packets are assigned to classes, in order to obtain a different treatment by the network; in particular, packets assigned to the most privileged class will be lost with a very small probability, while packets belonging to the lowest priority class will experience the traditional best–effort service. But the key problem in this solution is how to assign optimally video packets to the network classes. One way to perform the assignment is to proceed on a packet-by-packet basis, to exploit the highly non-uniform distortion impact of compressed video. Working on the distortion impact of each individual video packet has been shown in recent years to deliver better performance than relying on the average error sensitivity of each bitstream element. The distortion impact of a video packet can be expressed as the distortion that would be introduced at the receiver by its loss, taking into account the effects of both error concealment and error propagation due to temporal prediction. The estimation algorithms proposed in this dissertation are able to reproduce accurately the distortion envelope deriving from multiple losses on the network and the computational complexity required is negligible in respect to those proposed in literature. Several tests are run to validate the distortion estimation algorithms and to measure the influence of the main encoder-decoder settings. Different application scenarios are described and compared to demonstrate the benefits obtained using the developed algorithms. The packet distortion impact is inserted in each video packet and transmitted over the network where specialized agents manage the video packets using the distortion information. In particular, the internal structure of the agents is modified to allow video packets prioritization using primarily the distortion impact estimated by the transmitter. The results obtained will show that, in each scenario, a significant improvement may be obtained with respect to traditional transmission policies. The thesis is organized in two parts. The first provides the background material and represents the basics of the following arguments, while the other is dedicated to the original results obtained during the research activity. Referring to the first part in the first chapter it summarized an introduction to the principles and challenges for the multimedia transmission over packet networks. The most recent advances in video compression technologies are detailed in the second chapter, focusing in particular on aspects that involve the resilience to packet loss impairments. The third chapter deals with the main techniques adopted to protect the multimedia flow for mitigating the packet loss corruption due to channel failures. The fourth chapter introduces the more recent advances in network adaptive media transport detailing the techniques that prioritize the video packet flow. The fifth chapter makes a literature review of the existing distortion estimation techniques focusing mainly on their limitation aspects. The second part of the thesis describes the original results obtained in the modelling of the video distortion deriving from the transmission over an error prone network. In particular, the sixth chapter presents three new distortion estimation algorithms able to estimate the video quality and shows the results of some validation tests performed to measure the accuracy of the employed algorithms. The seventh chapter proposes different application scenarios where the developed algorithms may be used to enhance quickly the video quality at the end user side. Finally, the eight chapter summarizes the thesis contributions and remarks the most important conclusions. It also derives some directions for future improvements. The intent of the entire work presented hereafter is to develop some video distortion estimation algorithms able to predict the user quality deriving from the loss on the network as well as providing the results of some useful applications able to enhance the user experience during a video streaming session.Questa tesi di dottorato affronta il problema della trasmissione efficiente di contenuti multimediali su reti a pacchetto inaffidabili e con limitate risorse di banda. L’obiettivo è quello di ideare alcuni algoritmi in grado di predire l’andamento della qualità del video ricevuto da un utente e successivamente ideare alcune tecniche in grado di migliorare l’esperienza dell’utente finale nella fruizione dei servizi video. In particolare i contributi originali del presente lavoro riguardano lo sviluppo di algoritmi per la stima della distorsione e l’ideazione di alcuni scenari applicativi in molto frequenti dove poter valutare i benefici ottenibili applicando gli algoritmi di stima. I contributi presentati in questa tesi di dottorato sono il risultato degli studi compiuti con il gruppo di Telecomunicazioni del Dipartimento di Elettrotecnica Elettronica ed Informatica (DEEI) dell’Università degli Studi di Trieste durante il corso di dottorato in Ingegneria dell’Informazione. Negli ultimi anni la multimedialità, diffusa sulle reti cablate e wireless, sta diventando parte integrante del modo di utilizzare la rete diventando di fatto il fenomeno più imponente. Applicazioni come BitTorrent, la condivisione di file musicali e multimediali e il podcasting ad esempio costituiscono una parte significativa del traffico attuale su Internet. Quelle che negli ultimi anni erano le prime radio che trsmettevano sulla rete oggi si stanno evolvendo nei sistemi peer to peer per più avanzati per la diffusione della TV via web come CoolStreaming. Inoltre siti web come YouTube hanno costruito il loro business sulla memorizzazione/ distribuzione di video creati da chiunque abbia una semplice video camera. Un’altra caratteristica dell’imponente rivoluzione multimediale a cui stiamo assistendo è la diffusione dei video anche all’interno delle case dove i contenuti multimediali vengono distribuiti mediante delle reti wireless locali tra i vari dispositivi finali. Tutt’oggi è in corso una rivoluzione della multimedialità sulle reti IP con le radio, i televisioni, la telefonia e tutti i video che devono essere distribuiti sulle reti cablate e wireless verso utenti eterogenei. In generale la gran parte delle applicazioni multimediali richiedono una banda elevata e dei ritardi molto contenuti specialmente se le applicazioni sono di tipo interattivo. Sfortunatamente le reti wireless e Internet più in generale sono in grado di fornire un supporto limitato alle applicazioni multimediali. La variabilità di banda, di ritardo e nella perdita possono avere conseguenze gravi sulla qualità con cui viene ricevuto il video e questo può portare a una parziale insoddisfazione o addirittura alla rinuncia della fruizione da parte dell’utente finale. Le applicazioni multimediali sono spesso sensibili al ritardo e con requisiti di banda molto stringenti ma di fatto rimango tolleranti nei confronti delle perdite che possono avvenire durante la trasmissione. Al fine di superare le limitazioni è necessario sviluppare dei meccanismi di adattamento in grado di fare da ponte fra i requisiti delle applicazioni multimediali e le caratteristiche offerte dal livello di trasporto. Diversi approcci sono stati proposti in passato in letteratura per migliorare la trasmissione dei pacchetti riducendo le perdite; gli approcci variano dalle soluzioni di compressione efficiente all’aggiunta di ridondanza con tecniche di forward error correction e ritrasmissioni. Altre tecniche si basano sulla creazione di architetture di rete complesse in grado di garantire la QoS a livello rete dove router oppure altri agenti specializzati applicano diverse politiche di gestione del traffico in base ai valori contenuti nei campi dei pacchetti. Mediante queste architetture il traffico video viene marcato con delle classi di priorità al fine di creare una differenziazione nel traffico a livello rete; in particolare i pacchetti con i privilegi maggiori vengono assegnati alle classi di priorità più elevate e verranno persi con probabilità molto bassa mentre i pacchetti appartenenti alle classi di priorità inferiori saranno trattati alla stregua dei servizi di tipo best-effort. Uno dei principali problemi di questa soluzione riguarda come assegnare in maniera ottimale i singoli pacchetti video alle diverse classi di priorità. Un modo per effettuare questa classificazione è quello di procedere assegnando i pacchetti alle varie classi sulla base dell’importanza che ogni pacchetto ha sulla qualità finale. E’ stato dimostrato in numerosi lavori recenti che utilizzando come meccanismo per l’adattamento l’impatto sulla distorsione finale, porta significativi miglioramenti rispetto alle tecniche che utilizzano come parametro la sensibilità media del flusso nei confronti delle perdite. L’impatto che ogni pacchetto ha sulla qualità può essere espresso come la distorsione che viene introdotta al ricevitore se il pacchetto viene perso tenendo in considerazione gli effetti del recupero (error concealment) e la propagazione dell’errore (error propagation) caratteristica dei più recenti codificatori video. Gli algoritmi di stima della distorsione proposti in questa tesi sono in grado di riprodurre in maniera accurata l’inviluppo della distorsione derivante sia da perdite isolate che da perdite multiple nella rete con una complessità computazionale minima se confrontata con le più recenti tecniche di stima. Numerose prove sono stati effettuate al fine di validare gli algoritmi di stima e misurare l’influenza dei principali parametri di codifica e di decodifica. Al fine di enfatizzare i benefici ottenuti applicando gli algoritmi di stima della distorsione, durante la tesi verranno presentati alcuni scenari applicativi dove l’applicazione degli algoritmi proposti migliora sensibilmente la qualità finale percepita dagli utenti. Tali scenari verranno descritti, implementati e accuratamente valutati. In particolare, la distorsione stimata dal trasmettitore verrà incapsulata nei pacchetti video e, trasmessa nella rete dove agenti specializzati potranno agevolmente estrarla e utilizzarla come meccanismo rate-distortion per privilegiare alcuni pacchetti a discapito di altri. In particolare la struttura interna di un agente (un router) verrà modificata al fine di consentire la differenziazione del traffico utilizzando l’informazione dell’impatto che ogni pacchetto ha sulla qualità finale. I risultati ottenuti anche in termini di ridotta complessità computazionale in ogni scenario applicativo proposto mettono in luce i benefici derivanti dall’implementazione degli algoritmi di stima. La presenti tesi di dottorato è strutturata in due parti principali; la prima fornisce il background e rappresenta la base per tutti gli argomenti trattati nel seguito mentre la seconda parte è dedicata ai contributi originali e ai risultati ottenuti durante l’intera attività di ricerca. In riferimento alla prima parte in particolare un’introduzione ai principi e alle opportunità offerte dalla diffusione dei servizi multimediali sulle reti a pacchetto viene esposta nel primo capitolo. I progressi più recenti nelle tecniche di compressione video vengono esposti dettagliatamente nel secondo capitolo che si focalizza in particolare solo sugli aspetti che riguardano le tecniche per la mitigazione delle perdite. Il terzo capitolo introduce le principali tecniche per proteggere i flussi multimediali e ridurre le perdite causate dai fenomeni caratteristici del canale. Il quarto capitolo descrive i recenti avanzamenti nelle tecniche di network adaptive media transport illustrando i principali metodi utilizzati per differenziare il traffico video. Il quinto capitolo analizza i principali contributi nella letteratura sulle tecniche di stima della distorsione e si focalizza in particolare sulle limitazioni dei metodi attuali. La seconda parte della tesi descrive i contributi originali ottenuti nella modellizzazione della distorsione video derivante dalla trasmissione sulle reti con perdite. In particolare il sesto capitolo presenta tre nuovi algoritmi in grado di riprodurre fedelmente l’inviluppo della distorsione video. I numerosi test e risultati verranno proposti al fine di validare gli algoritmi e misurare l’accuratezza nella stima. Il settimo capitolo propone diversi scenari applicativi dove gli algoritmi sviluppati possono essere utilizzati per migliorare in maniera significativa la qualità percepita dall’utente finale. Infine l’ottavo capitolo sintetizza l’intero lavoro svolto e i principali risultati ottenuti. Nello stesso capitolo vengono inoltre descritti gli sviluppi futuri dell’attività di ricerca. L’obiettivo dell’intero lavoro presentato è quello di mostrare i benefici derivanti dall’utilizzo di nuovi algoritmi per la stima della distorsione e di fornire alcuni scenari applicativi di utilizzo.XIX Ciclo197

Combined Source and Channel Strategies for Optimized Video Communications

ISBN 978-953-7619-70-

Error-resilient multi-view video plus depth based 3-D video coding

Three Dimensional (3-D) video, by definition, is a collection of signals that can provide depth perception of a 3-D scene. With the development of 3-D display technologies and interactive multimedia systems, 3-D video has attracted significant interest from both industries and academia with a variety of applications. In order to provide desired services in various 3-D video applications, the multiview video plus depth (MVD) representation, which can facilitate the generation of virtual views, has been determined to be the best format for 3-D video data. Similar to 2-D video, compressed 3-D video is highly sensitive to transmission errors due to errors propagated from the current frame to the future predicted frames. Moreover, since the virtual views required for auto-stereoscopic displays are rendered from the compressed texture videos and depth maps, transmission errors of the distorted texture videos and depth maps can be further propagated to the virtual views. Besides, the distortions in texture and depth show different effects on the rendering views. Therefore, compared to the reliability of the transmission of the 2-D video, error-resilient texture video and depth map coding are facing major new challenges. This research concentrates on improving the error resilience performance of MVD-based 3-D video in packet loss scenarios. Based on the analysis of the propagating behaviour of transmission errors, a Wyner-Ziv (WZ)-based error-resilient algorithm is first designed for coding of the multi-view video data or depth data. In this scheme, an auxiliary redundant stream encoded according to WZ principle is employed to protect a primary stream encoded with standard multi-view video coding codec. Then, considering the fact that different combinations of texture and depth coding mode will exhibit varying robustness to transmission errors, a rate-distortion optimized mode switching scheme is proposed to strike the optimal trade-off between robustness and compression effciency. In this approach, the texture and depth modes are jointly optimized by minimizing the overall distortion of both the coded and synthesized views subject to a given bit rate. Finally, this study extends the research on the reliable transmission of view synthesis prediction (VSP)-based 3-D video. In order to mitigate the prediction position error caused by packet losses in the depth map, a novel disparity vector correction algorithm is developed, where the corrected disparity vector is calculated from the depth error. To facilitate decoder error concealment, the depth error is recursively estimated at the decoder. The contributions of this dissertation are multifold. First, the proposed WZbased error-resilient algorithm can accurately characterize the effect of transmission error on multi-view distortion at the transform domain in consideration of both temporal and inter-view error propagation, and based on the estimated distortion, this algorithm can perform optimal WZ bit allocation at the encoder through explicitly developing a sophisticated rate allocation strategy. This proposed algorithm is able to provide a finer granularity in performing rate adaptivity and unequal error protection for multi-view data, not only at the frame level, but also at the bit-plane level. Secondly, in the proposed mode switching scheme, a new analytic model is formulated to optimally estimate the view synthesis distortion due to packet losses, in which the compound impact of the transmission distortions of both the texture video and the depth map on the quality of the synthesized view is mathematically analysed. The accuracy of this view synthesis distortion model is demonstrated via simulation results and, further, the estimated distortion is integrated into a rate-distortion framework for optimal mode switching to achieve substantial performance gains over state-of-the-art algorithms. Last, but not least, this dissertation provides a preliminary investigation of VSP-based 3-D video over unreliable channel. In the proposed disparity vector correction algorithm, the pixel-level depth map error can be precisely estimated at the decoder without the deterministic knowledge of the error-free reconstructed depth. The approximation of the innovation term involved in depth error estimation is proved theoretically. This algorithm is very useful to conceal the position-erroneous pixels whose disparity vectors are correctly received

Robust density modelling using the student's t-distribution for human action recognition

The extraction of human features from videos is often inaccurate and prone to outliers. Such outliers can severely affect density modelling when the Gaussian distribution is used as the model since it is highly sensitive to outliers. The Gaussian distribution is also often used as base component of graphical models for recognising human actions in the videos (hidden Markov model and others) and the presence of outliers can significantly affect the recognition accuracy. In contrast, the Student's t-distribution is more robust to outliers and can be exploited to improve the recognition rate in the presence of abnormal data. In this paper, we present an HMM which uses mixtures of t-distributions as observation probabilities and show how experiments over two well-known datasets (Weizmann, MuHAVi) reported a remarkable improvement in classification accuracy. © 2011 IEEE

Enhanced quality reconstruction of erroneous video streams using packet filtering based on non-desynchronizing bits and UDP checksum-filtered list decoding

The latest video coding standards, such as H.264 and H.265, are extremely vulnerable in error-prone networks. Due to their sophisticated spatial and temporal prediction tools, the effect of an error is not limited to the erroneous area but it can easily propagate spatially to the neighboring blocks and temporally to the following frames. Thus, reconstructed video packets at the decoder side may exhibit significant visual quality degradation. Error concealment and error corrections are two mechanisms that have been developed to improve the quality of reconstructed frames in the presence of errors. In most existing error concealment approaches, the corrupted packets are ignored and only the correctly received information of the surrounding areas (spatially and/or temporally) is used to recover the erroneous area. This is due to the fact that there is no perfect error detection mechanism to identify correctly received blocks within a corrupted packet, and moreover because of the desynchronization problem caused by the transmission errors on the variable-length code (VLC). But, as many studies have shown, the corrupted packets may contain valuable information that can be used to reconstruct adequately of the lost area (e.g. when the error is located at the end of a slice). On the other hand, error correction approaches, such as list decoding, exploit the corrupted packets to generate several candidate transmitted packets from the corrupted received packet. They then select, among these candidates, the one with the highest likelihood of being the transmitted packet based on the available soft information (e.g. log-likelihood ratio (LLR) of each bit). However, list decoding approaches suffer from a large solution space of candidate transmitted packets. This is worsened when the soft information is not available at the application layer; a more realistic scenario in practice. Indeed, since it is unknown which bits have higher probabilities of having been modified during transmission, the candidate received packets cannot be ranked by likelihood. In this thesis, we propose various strategies to improve the quality of reconstructed packets which have been lightly damaged during transmission (e.g. at most a single error per packet). We first propose a simple but efficient mechanism to filter damaged packets in order to retain those likely to lead to a very good reconstruction and discard the others. This method can be used as a complement to most existing concealment approaches to enhance their performance. The method is based on the novel concept of non-desynchronizing bits (NDBs) defined, in the context of an H.264 context-adaptive variable-length coding (CAVLC) coded sequence, as a bit whose inversion does not cause desynchronization at the bitstream level nor changes the number of decoded macroblocks. We establish that, on typical coded bitstreams, the NDBs constitute about a one-third (about 30%) of a bitstream, and that the effect on visual quality of flipping one of them in a packet is mostly insignificant. In most cases (90%), the quality of the reconstructed packet when modifying an individual NDB is almost the same as the intact one. We thus demonstrate that keeping, under certain conditions, a corrupted packet as a candidate for the lost area can provide better visual quality compared to the concealment approaches. We finally propose a non-desync-based decoding framework, which retains a corrupted packet, under the condition of not causing desynchronization and not altering the number of expected macroblocks. The framework can be combined with most current concealment approaches. The proposed approach is compared to the frame copy (FC) concealment of Joint Model (JM) software (JM-FC) and a state-of-the-art concealment approach using the spatiotemporal boundary matching algorithm (STBMA) mechanism, in the case of one bit in error, and on average, respectively, provides 3.5 dB and 1.42 dB gain over them. We then propose a novel list decoding approach called checksum-filtered list decoding (CFLD) which can correct a packet at the bit stream level by exploiting the receiver side user datagram protocol (UDP) checksum value. The proposed approach is able to identify the possible locations of errors by analyzing the pattern of the calculated UDP checksum on the corrupted packet. This makes it possible to considerably reduce the number of candidate transmitted packets in comparison to conventional list decoding approaches, especially when no soft information is available. When a packet composed of N bits contains a single bit in error, instead of considering N candidate packets, as is the case in conventional list decoding approaches, the proposed approach considers approximately N/32 candidate packets, leading to a 97% reduction in the number of candidates. This reduction can increase to 99.6% in the case of a two-bit error. The method’s performance is evaluated using H.264 and high efficiency video coding (HEVC) test model software. We show that, in the case H.264 coded sequence, on average, the CFLD approach is able to correct the packet 66% of the time. It also offers a 2.74 dB gain over JM-FC and 1.14 dB and 1.42 dB gains over STBMA and hard output maximum likelihood decoding (HO-MLD), respectively. Additionally, in the case of HEVC, the CFLD approach corrects the corrupted packet 91% of the time, and offers 2.35 dB and 4.97 dB gains over our implementation of FC concealment in HEVC test model software (HM-FC) in class B (1920×1080) and C (832×480) sequences, respectively

Video modeling via implicit motion representations

Video modeling refers to the development of analytical representations for explaining the intensity distribution in video signals. Based on the analytical representation, we can develop algorithms for accomplishing particular video-related tasks. Therefore video modeling provides us a foundation to bridge video data and related-tasks. Although there are many video models proposed in the past decades, the rise of new applications calls for more efficient and accurate video modeling approaches.;Most existing video modeling approaches are based on explicit motion representations, where motion information is explicitly expressed by correspondence-based representations (i.e., motion velocity or displacement). Although it is conceptually simple, the limitations of those representations and the suboptimum of motion estimation techniques can degrade such video modeling approaches, especially for handling complex motion or non-ideal observation video data. In this thesis, we propose to investigate video modeling without explicit motion representation. Motion information is implicitly embedded into the spatio-temporal dependency among pixels or patches instead of being explicitly described by motion vectors.;Firstly, we propose a parametric model based on a spatio-temporal adaptive localized learning (STALL). We formulate video modeling as a linear regression problem, in which motion information is embedded within the regression coefficients. The coefficients are adaptively learned within a local space-time window based on LMMSE criterion. Incorporating a spatio-temporal resampling and a Bayesian fusion scheme, we can enhance the modeling capability of STALL on more general videos. Under the framework of STALL, we can develop video processing algorithms for a variety of applications by adjusting model parameters (i.e., the size and topology of model support and training window). We apply STALL on three video processing problems. The simulation results show that motion information can be efficiently exploited by our implicit motion representation and the resampling and fusion do help to enhance the modeling capability of STALL.;Secondly, we propose a nonparametric video modeling approach, which is not dependent on explicit motion estimation. Assuming the video sequence is composed of many overlapping space-time patches, we propose to embed motion-related information into the relationships among video patches and develop a generic sparsity-based prior for typical video sequences. First, we extend block matching to more general kNN-based patch clustering, which provides an implicit and distributed representation for motion information. We propose to enforce the sparsity constraint on a higher-dimensional data array signal, which is generated by packing the patches in the similar patch set. Then we solve the inference problem by updating the kNN array and the wanted signal iteratively. Finally, we present a Bayesian fusion approach to fuse multiple-hypothesis inferences. Simulation results in video error concealment, denoising, and deartifacting are reported to demonstrate its modeling capability.;Finally, we summarize the proposed two video modeling approaches. We also point out the perspectives of implicit motion representations in applications ranging from low to high level problems

MAP Joint Source-Channel Arithmetic Decoding for Compressed Video

In order to have robust video transmission over error prone telecommunication channels several mechanisms are introduced. These mechanisms try to detect, correct or conceal the errors in the received video stream. In this thesis, the performance of the video codec is improved in terms of error rates without increasing overhead in terms of data bit rate. This is done by exploiting the residual syntactic/semantic redundancy inside compressed video along with optimizing the configuration of the state-of-the art entropy coding, i.e., binary arithmetic coding, and optimizing the quantization of the channel output. The thesis is divided into four phases. In the first phase, a breadth-first suboptimal sequential maximum a posteriori (MAP) decoder is employed for joint source-channel arithmetic decoding of H.264 symbols. The proposed decoder uses not only the intentional redundancy inserted via a forbidden symbol (FS) but also exploits residual redundancy by a syntax checker. In contrast to previous methods this is done as each channel bit is decoded. Simulations using intra prediction modes show improvements in error rates, e.g., syntax element error rate reduction by an order of magnitude for channel SNR of 7.33dB. The cost of this improvement is more computational complexity spent on the syntax checking. In the second phase, the configuration of the FS in the symbol set is studied. The delay probability function, i.e., the probability of the number of bits required to detect an error, is calculated for various FS configurations. The probability of missed error detection is calculated as a figure of merit for optimizing the FS configuration. The simulation results show the effectiveness of the proposed figure of merit, and support the FS configuration in which the FS lies entirely between the other information carrying symbols to be the best. In the third phase, a new method for estimating the a priori probability of particular syntax elements is proposed. This estimation is based on the interdependency among the syntax elements that were previously decoded. This estimation is categorized as either reliable or unreliable. The decoder uses this prior information when they are reliable, otherwise the MAP decoder considers that the syntax elements are equiprobable and in turn uses maximum likelihood (ML) decoding. The reliability detection is carried out using a threshold on the local entropy of syntax elements in the neighboring macroblocks. In the last phase, a new measure to assess performance of the channel quantizer is proposed. This measure is based on the statistics of the rank of true candidate among the sorted list of candidates in the MAP decoder. Simulation results shows that a quantizer designed based on the proposed measure is superior to the quantizers designed based on maximum mutual information and minimum mean square error