10 research outputs found

    Selected topics in video coding and computer vision

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    Video applications ranging from multimedia communication to computer vision have been extensively studied in the past decades. However, the emergence of new applications continues to raise questions that are only partially answered by existing techniques. This thesis studies three selected topics related to video: intra prediction in block-based video coding, pedestrian detection and tracking in infrared imagery, and multi-view video alignment.;In the state-of-art video coding standard H.264/AVC, intra prediction is defined on the hierarchical quad-tree based block partitioning structure which fails to exploit the geometric constraint of edges. We propose a geometry-adaptive block partitioning structure and a new intra prediction algorithm named geometry-adaptive intra prediction (GAIP). A new texture prediction algorithm named geometry-adaptive intra displacement prediction (GAIDP) is also developed by extending the original intra displacement prediction (IDP) algorithm with the geometry-adaptive block partitions. Simulations on various test sequences demonstrate that intra coding performance of H.264/AVC can be significantly improved by incorporating the proposed geometry adaptive algorithms.;In recent years, due to the decreasing cost of thermal sensors, pedestrian detection and tracking in infrared imagery has become a topic of interest for night vision and all weather surveillance applications. We propose a novel approach for detecting and tracking pedestrians in infrared imagery based on a layered representation of infrared images. Pedestrians are detected from the foreground layer by a Principle Component Analysis (PCA) based scheme using the appearance cue. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm. Simulations with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithms.;Multi-view video alignment is a process to facilitate the fusion of non-synchronized multi-view video sequences for various applications including automatic video based surveillance and video metrology. In this thesis, we propose an accurate multi-view video alignment algorithm that iteratively aligns two sequences in space and time. To achieve an accurate sub-frame temporal alignment, we generalize the existing phase-correlation algorithm to 3-D case. We also present a novel method to obtain the ground-truth of the temporal alignment by using supplementary audio signals sampled at a much higher rate. The accuracy of our algorithm is verified by simulations using real-world sequences

    Video object segmentation for interactive multimedia

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    Ankara : Department of Electrical and Electronics Engineering and Institute of Engineering and Sciences, Bilkent Univ., 1998.Thesis (Master's) -- Bilkent University, 1998.Includes bibliographical references leaves 67-74.Recently, trends in video processing research have shifted from video compression to video analysis, due to the emerging standards MPEG-4 and MPEG-7. These standards will enable the users to interact with the objects in the audiovisual scene generated at the user’s end. However, neither of them prescribes how to obtain the objects. Many methods have been proposed for segmentation of video objects. One of the approaches is the “Analysis Model” (AM) of European COST-211 project. It is a modular approach to video object segmentation problem. Although AM performs acceptably in some cases, the results in many other cases are not good enough to be considered as semantic objects. In this thesis, a new tool is integrated and some modules are replaced by improved versions. One of the tools uses a block-based motion estimation technique to analyze the motion content within a scene, computes a motion activity parameter, and skips frames accordingly. Also introduced is a powerful motion estimation method which uses maximum a posteriori probability (MAP) criterion and Gibbs energies to obtain more reliable motion vectors and to calculate temporally unpredictable areas. To handle more complex motion in the scene, the 2-D affine motion model is added to the motion segmentation module, which employs only the translational model. The observed results indicate that the AM performance is improved substantially. The objects in the scene and their boundaries are detected more accurately, compared to the previous results.Ekmekçi, TolgaM.S

    Adaptive video delivery using semantics

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    The diffusion of network appliances such as cellular phones, personal digital assistants and hand-held computers has created the need to personalize the way media content is delivered to the end user. Moreover, recent devices, such as digital radio receivers with graphics displays, and new applications, such as intelligent visual surveillance, require novel forms of video analysis for content adaptation and summarization. To cope with these challenges, we propose an automatic method for the extraction of semantics from video, and we present a framework that exploits these semantics in order to provide adaptive video delivery. First, an algorithm that relies on motion information to extract multiple semantic video objects is proposed. The algorithm operates in two stages. In the first stage, a statistical change detector produces the segmentation of moving objects from the background. This process is robust with regard to camera noise and does not need manual tuning along a sequence or for different sequences. In the second stage, feedbacks between an object partition and a region partition are used to track individual objects along the frames. These interactions allow us to cope with multiple, deformable objects, occlusions, splitting, appearance and disappearance of objects, and complex motion. Subsequently, semantics are used to prioritize visual data in order to improve the performance of adaptive video delivery. The idea behind this approach is to organize the content so that a particular network or device does not inhibit the main content message. Specifically, we propose two new video adaptation strategies. The first strategy combines semantic analysis with a traditional frame-based video encoder. Background simplifications resulting from this approach do not penalize overall quality at low bitrates. The second strategy uses metadata to efficiently encode the main content message. The metadata-based representation of object's shape and motion suffices to convey the meaning and action of a scene when the objects are familiar. The impact of different video adaptation strategies is then quantified with subjective experiments. We ask a panel of human observers to rate the quality of adapted video sequences on a normalized scale. From these results, we further derive an objective quality metric, the semantic peak signal-to-noise ratio (SPSNR), that accounts for different image areas and for their relevance to the observer in order to reflect the focus of attention of the human visual system. At last, we determine the adaptation strategy that provides maximum value for the end user by maximizing the SPSNR for given client resources at the time of delivery. By combining semantic video analysis and adaptive delivery, the solution presented in this dissertation permits the distribution of video in complex media environments and supports a large variety of content-based applications

    A family of stereoscopic image compression algorithms using wavelet transforms

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    With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. In the proposed CODEC I, block-based disparity estimation/compensation (DE/DC) is performed in pixel domain. However, this results in an inefficiency when DWT is applied on the whole predictive error image that results from the DE process. This is because of the existence of artificial block boundaries between error blocks in the predictive error image. To overcome this problem, in the remaining proposed CODECs, DE/DC is performed in the wavelet domain. Due to the multiresolution nature of the wavelet domain, two methods of disparity estimation and compensation have been proposed. The first method is performing DEJDC in each subband of the lowest/coarsest resolution level and then propagating the disparity vectors obtained to the corresponding subbands of higher/finer resolution. Note that DE is not performed in every subband due to the high overhead bits that could be required for the coding of disparity vectors of all subbands. This method is being used in CODEC II. In the second method, DEJDC is performed m the wavelet-block domain. This enables disparity estimation to be performed m all subbands simultaneously without increasing the overhead bits required for the coding disparity vectors. This method is used by CODEC III. However, performing disparity estimation/compensation in all subbands would result in a significant improvement of CODEC III. To further improve the performance of CODEC ill, pioneering wavelet-block search technique is implemented in CODEC IV. The pioneering wavelet-block search technique enables the right/predicted image to be reconstructed at the decoder end without the need of transmitting the disparity vectors. In proposed CODEC V, pioneering block search is performed in all subbands of DWT decomposition which results in an improvement of its performance. Further, the CODEC IV and V are able to perform at very low bit rates(< 0.15 bpp). In CODEC VI and CODEC VII, Overlapped Block Disparity Compensation (OBDC) is used with & without the need of coding disparity vector. Our experiment results showed that no significant coding gains could be obtained for these CODECs over CODEC IV & V. All proposed CODECs m this thesis are wavelet-based stereo image coding algorithms that maximise the flexibility and benefits offered by wavelet transform technology when applied to stereo imaging. In addition the use of a baseline-JPEG coding architecture would enable the easy adaptation of the proposed algorithms within systems originally built for DCT-based coding. This is an important feature that would be useful during an era where DCT-based technology is only slowly being phased out to give way for DWT based compression technology. In addition, this thesis proposed a stereo image coding algorithm that uses JPEG-2000 technology as the basic compression engine. The proposed CODEC, named RASTER is a rate scalable stereo image CODEC that has a unique ability to preserve the image quality at binocular depth boundaries, which is an important requirement in the design of stereo image CODEC. The experimental results have shown that the proposed CODEC is able to achieve PSNR gains of up to 3.7 dB as compared to directly transmitting the right frame using JPEG-2000

    A family of stereoscopic image compression algorithms using wavelet transforms

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    With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2-D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. [Continues.

    Securing Multi-Layer Communications: A Signal Processing Approach

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    Security is becoming a major concern in this information era. The development in wireless communications, networking technology, personal computing devices, and software engineering has led to numerous emerging applications whose security requirements are beyond the framework of conventional cryptography. The primary motivation of this dissertation research is to develop new approaches to the security problems in secure communication systems, without unduly increasing the complexity and cost of the entire system. Signal processing techniques have been widely applied in communication systems. In this dissertation, we investigate the potential, the mechanism, and the performance of incorporating signal processing techniques into various layers along the chain of secure information processing. For example, for application-layer data confidentiality, we have proposed atomic encryption operations for multimedia data that can preserve standard compliance and are friendly to communications and delegate processing. For multimedia authentication, we have discovered the potential key disclosure problem for popular image hashing schemes, and proposed mitigation solutions. In physical-layer wireless communications, we have discovered the threat of signal garbling attack from compromised relay nodes in the emerging cooperative communication paradigm, and proposed a countermeasure to trace and pinpoint the adversarial relay. For the design and deployment of secure sensor communications, we have proposed two sensor location adjustment algorithms for mobility-assisted sensor deployment that can jointly optimize sensing coverage and secure communication connectivity. Furthermore, for general scenarios of group key management, we have proposed a time-efficient key management scheme that can improve the scalability of contributory key management from O(log n) to O(log(log n)) using scheduling and optimization techniques. This dissertation demonstrates that signal processing techniques, along with optimization, scheduling, and beneficial techniques from other related fields of study, can be successfully integrated into security solutions in practical communication systems. The fusion of different technical disciplines can take place at every layer of a secure communication system to strengthen communication security and improve performance-security tradeoff

    Efficient acquisition, representation and rendering of light fields

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    In this thesis we discuss the representation of three-dimensional scenes using image data (image-based rendering), and more precisely the so-called light field approach. We start with an up-to-date survey on previous work in this young field of research. Then we propose a light field representation based on image data and additional per-pixel depth values. This enables us to reconstruct arbitrary views of the scene in an efficient way and with high quality. Furtermore, we can use the same representation to determine optimal reference views during the acquisition of a light field. We further present the so-called free form parameterization, which allows for a relatively free placement of reference views. Finally, we demonstrate a prototype of the Lumi-Shelf system, which acquires, transmits, and renders the light field of a dynamic scene at multiple frames per second.Diese Doktorarbeit beschäftigt sich mit der Repräsentierung dreidimensionaler Szenen durch Bilddaten (engl. image-based rendering, deutsch bildbasierte Bildsynthese), speziell mit dem Ansatz des sog. Lichtfelds. Nach einem aktuellen Überblick über bisherige Arbeiten in diesem jungen Forschungsgebiet stellen wir eine Datenrepräsentation vor, die auf Bilddaten mit zusätzlichen Tiefenwerten basiert. Damit sind wir in der Lage, beliebige Ansichten der Szene effizient und in hoher Qualität zu rekonstruieren sowie die optimalen Referenz-Ansichten bei der Akquisition eines Lichtfelds zu bestimmen. Weiterhin präsentieren wir die sog. Freiform-Parametrisierung, die eine relativ freie Anordnung der Referenz-Ansichten erlaubt. Abschließend demonstrieren wir einen Prototyp des Lumishelf-Systems, welches die Aufnahme, Übertragung und Darstellung des Lichtfeldes einer dynamischen Szene mit mehreren Bildern pro Sekunde ermöglicht

    Efficient acquisition, representation and rendering of light fields

    Get PDF
    In this thesis we discuss the representation of three-dimensional scenes using image data (image-based rendering), and more precisely the so-called light field approach. We start with an up-to-date survey on previous work in this young field of research. Then we propose a light field representation based on image data and additional per-pixel depth values. This enables us to reconstruct arbitrary views of the scene in an efficient way and with high quality. Furtermore, we can use the same representation to determine optimal reference views during the acquisition of a light field. We further present the so-called free form parameterization, which allows for a relatively free placement of reference views. Finally, we demonstrate a prototype of the Lumi-Shelf system, which acquires, transmits, and renders the light field of a dynamic scene at multiple frames per second.Diese Doktorarbeit beschäftigt sich mit der Repräsentierung dreidimensionaler Szenen durch Bilddaten (engl. image-based rendering, deutsch bildbasierte Bildsynthese), speziell mit dem Ansatz des sog. Lichtfelds. Nach einem aktuellen Überblick über bisherige Arbeiten in diesem jungen Forschungsgebiet stellen wir eine Datenrepräsentation vor, die auf Bilddaten mit zusätzlichen Tiefenwerten basiert. Damit sind wir in der Lage, beliebige Ansichten der Szene effizient und in hoher Qualität zu rekonstruieren sowie die optimalen Referenz-Ansichten bei der Akquisition eines Lichtfelds zu bestimmen. Weiterhin präsentieren wir die sog. Freiform-Parametrisierung, die eine relativ freie Anordnung der Referenz-Ansichten erlaubt. Abschließend demonstrieren wir einen Prototyp des Lumishelf-Systems, welches die Aufnahme, Übertragung und Darstellung des Lichtfeldes einer dynamischen Szene mit mehreren Bildern pro Sekunde ermöglicht
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