Automatic human face detection in color images

Automatic human face detection in digital image has been an active area of research over the past decade. Among its numerous applications, face detection plays a key role in face recognition system for biometric personal identification, face tracking for intelligent human computer interface (HCI), and face segmentation for object-based video coding. Despite significant progress in the field in recent years, detecting human faces in unconstrained and complex images remains a challenging problem in computer vision. An automatic system that possesses a similar capability as the human vision system in detecting faces is still a far-reaching goal. This thesis focuses on the problem of detecting human laces in color images. Although many early face detection algorithms were designed to work on gray-scale Images, strong evidence exists to suggest face detection can be done more efficiently by taking into account color characteristics of the human face. In this thesis, we present a complete and systematic face detection algorithm that combines the strengths of both analytic and holistic approaches to face detection. The algorithm is developed to detect quasi-frontal faces in complex color Images. This face class, which represents typical detection scenarios in most practical applications of face detection, covers a wide range of face poses Including all in-plane rotations and some out-of-plane rotations. The algorithm is organized into a number of cascading stages including skin region segmentation, face candidate selection, and face verification. In each of these stages, various visual cues are utilized to narrow the search space for faces. In this thesis, we present a comprehensive analysis of skin detection using color pixel classification, and the effects of factors such as the color space, color classification algorithm on segmentation performance. We also propose a novel and efficient face candidate selection technique that is based on color-based eye region detection and a geometric face model. This candidate selection technique eliminates the computation-intensive step of window scanning often employed In holistic face detection, and simplifies the task of detecting rotated faces. Besides various heuristic techniques for face candidate verification, we developface/nonface classifiers based on the naive Bayesian model, and investigate three feature extraction schemes, namely intensity, projection on face subspace and edge-based. Techniques for improving face/nonface classification are also proposed, including bootstrapping, classifier combination and using contextual information. On a test set of face and nonface patterns, the combination of three Bayesian classifiers has a correct detection rate of 98.6% at a false positive rate of 10%. Extensive testing results have shown that the proposed face detector achieves good performance in terms of both detection rate and alignment between the detected faces and the true faces. On a test set of 200 images containing 231 faces taken from the ECU face detection database, the proposed face detector has a correct detection rate of 90.04% and makes 10 false detections. We have found that the proposed face detector is more robust In detecting in-plane rotated laces, compared to existing face detectors. +D2

Multiperspective mosaics and layered representation for scene visualization

This thesis documents the efforts made to implement multiperspective mosaicking for the purpose of mosaicking undervehicle and roadside sequences. For the undervehicle sequences, it is desired to create a large, high-resolution mosaic that may used to quickly inspect the entire scene shot by a camera making a single pass underneath the vehicle. Several constraints are placed on the video data, in order to facilitate the assumption that the entire scene in the sequence exists on a single plane. Therefore, a single mosaic is used to represent a single video sequence. Phase correlation is used to perform motion analysis in this case. For roadside video sequences, it is assumed that the scene is composed of several planar layers, as opposed to a single plane. Layer extraction techniques are implemented in order to perform this decomposition. Instead of using phase correlation to perform motion analysis, the Lucas-Kanade motion tracking algorithm is used in order to create dense motion maps. Using these motion maps, spatial support for each layer is determined based on a pre-initialized layer model. By separating the pixels in the scene into motion-specific layers, it is possible to sample each element in the scene correctly while performing multiperspective mosaicking. It is also possible to fill in many gaps in the mosaics caused by occlusions, hence creating more complete representations of the objects of interest. The results are several mosaics with each mosaic representing a single planar layer of the scene

Vector quantization for spatiotemporal sub-band coding

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1990.Includes bibliographical references (leaves 111-115).by Pasquale Romano, Jr.M.S

A wearable system that learns a kinematic model and finds structure in everyday manipulation by using absolute orientation sensors and a camera

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 215-220).This thesis presents Duo, the first wearable system to autonomously learn a kinematic model of the wearer via body-mounted absolute orientation sensors and a head-mounted camera. With Duo, we demonstrate the significant benefits of endowing a wearable system with the ability to sense the kinematic configuration of the wearer's body. We also show that a kinematic model can be autonomously estimated offline from less than an hour of recorded video and orientation data from a wearer performing unconstrained, unscripted, household activities within a real, unaltered, home environment. We demonstrate that our system for autonomously estimating this kinematic model places very few constraints on the wearer's body, the placement of the sensors, and the appearance of the hand, which, for example, allows it to automatically discover a left-handed kinematic model for a left-handed wearer, and to automatically compensate for distinct camera mounts, and sensor configurations. Furthermore, we show that this learned kinematic model efficiently and robustly predicts the location of the dominant hand within video from the head-mounted camera even in situations where vision-based hand detectors would be likely to fail.(cont.) Additionally, we show ways in which the learned kinematic model can facilitate highly efficient processing of large databases of first person experience. Finally, we show that the kinematic model can efficiently direct visual processing so as to acquire a large number of high quality segments of the wearer's hand and the manipulated objects. Within the course of justifying these claims, we present methods for estimating global image motion, segmenting foreground motion, segmenting manipulation events, finding and representing significant hand postures, segmenting visual regions, and detecting visual points of interest with associated shape descriptors. We also describe our architecture and user-level application for machine augmented annotation and browsing of first person video and absolute orientations. Additionally, we present a real-time application in which the human and wearable cooperate through tightly integrated behaviors coordinated by the wearable's kinematic perception, and together acquire high-quality visual segments of manipulable objects that interest the wearable.by Charles Clark Kemp.Ph.D

Adaptive equalisation for fading digital communication channels

This thesis considers the design of new adaptive equalisers for fading digital communication channels. The role of equalisation is discussed in the context of the functions of a digital radio communication system and both conventional and more recent novel equaliser designs are described. The application of recurrent neural networks to the problem of equalisation is developed from a theoretical study of a single node structure to the design of multinode structures. These neural networks are shown to cancel intersymbol interference in a manner mimicking conventional techniques and simulations demonstrate their sensitivity to symbol estimation errors. In addition the error mechanisms of conventional maximum likelihood equalisers operating on rapidly time-varying channels are investigated and highlight the problems of channel estimation using delayed and often incorrect symbol estimates. The relative sensitivity of Bayesian equalisation techniques to errors in the channel estimate is studied and demonstrates that the structure's equalisation capability is also susceptible to such errors. Applications of multiple channel estimator methods are developed, leading to reduced complexity structures which trade performance for a smaller computational load. These novel structures are shown to provide an improvement over the conventional techniques, especially for rapidly time-varying channels, by reducing the time delay in the channel estimation process. Finally, the use of confidence measures of the equaliser's symbol estimates in order to improve channel estimation is studied and isolates the critical areas in the development of the technique — the production of reliable confidence measures by the equalisers and the statistics of symbol estimation error bursts

Communication platform for inter-satellite links in distributed satellite systems

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

2016 - The Twenty-first Annual Symposium of Student Scholars

The full program book from the Twenty-first Annual Symposium of Student Scholars, held on April 21, 2016. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1015/thumbnail.jp

Auditory group theory with applications to statistical basis methods for structured audio

Thesis (Ph. D.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1998.Includes bibliographical references (p. 161-172).Michael Anthony Casey.Ph.D

Interface air pour systèmes de navigation en bande S : étude détaillée des signaux OFDM

Positioning in urban or indoor environment is a hot topic, either due to regulations such as the E911 requiring US mobile telecommunication operators to be able to locate their subscribers in case of emergency, or due to the market development, with the extension of location - based services targeting the mass market concentrated in metropolitan areas. In urban or indoor areas, it is generally recognized that satellite - based positioning systems are not suitable (alone) to provide a continuous, reliable and accurate position to the user. Therefore, alternative positioning techniques may be useful to complement or replace satellite positioning in these environments. This PhD study ha s studied the possibility of using a mobile TV system based on the DVB - SH standard as system of opportunity for positioning. The advantage s of using a DVB - SH system for positioning are multiple. First, such system has a good availability in metropolitan areas, including indoor. Secondly, the emitters are synchronized and their density should be sufficient to track signals from several emitters simultaneously. This opens the possibility of using timing measurements from several emitters to find a position by trilateration . Also, the large bandwidth of the TV signal, required for the transmission of video content, should be beneficial for the accuracy of the timing measurements and for the robustness against multipath . Therefore, DVB - SH system seems to be an interesting candidate as system of opportunity for positioning. However, several challenges are to be solved for such a solution to be relevant. First, the signals propagate in the urban environment, which creates challenging conditions for positioning su ch as strong power fading, blockage of the desired line - of - sight signal or large echoes. Secondly, the DVB - SH standard uses an OFDM modulation, which has not been studied for positioning purpose. Therefore, techniques for fine tracking of the first receive d signal replica will have to be developed. Finally, a particularity of modern broadcast system is the use of a Single Frequency Network, in which all emitters send the same signal on the same carrier frequency. Therefore emitter identification in a Single Frequency will be another issue to be solved. This PhD study has proved the feasibility of positioning using DVB - SH signals. The main contributions of this work are the propositions of (1) an OFDM signal delay tracking method working in urban propagation channels, and (2) a modification to the network deployment permitting emitter identification and (3) a first assessment of the position accuracy using the proposed algorithms. These two methods have very low impact on the initial TV broadcasting service if the right set of signal parameters is chosen: no signal modification is required and the network deployment modification uses a feature already present in the DVB - SH standard. The positioning method was simulated using real urban propagation channel measurements. The obtained position has root mean square error of 4 0m. The main error contribution comes from tracking a non - line - of - sight signal. Further work would be required to deal with this issue, which would lower the position root mean square error to 7 m, which has been locally observed in the simulation for good tracking conditionsLe positionnement en environnement urbain est un domaine de recherche actif, de par la croissance des services grand public liées à la localisation, et à cause de réglementations émergentes liées aux situations d'urgence (E911). En environnement urbain ou à l'intérieur des bâtiments, il est communément admis que les systèmes de positionnement basés sur des satellites ne sont pas suffisants pour fournir une position précise, fiable et de manière continue. Des techniques de positionnement alternatives sont donc développées afin de remplacer ou compléter les systèmes de positionnement par satellite. Cette thèse étudie la possibilité de fournir un service de positionnement utilisant un futur système de diffusion de télévison vers les mobiles basé sur le standard DVB-SH. Le principal attrait de ce système pour du positionnement est sa bonne couverture en milieu urbain, ainsi que l'utilisation d'un réseau d'émetteurs synchronisés. Il est donc possible d'employer des mesures de temps d'arrivée des signaux afin de réaliser une triangulation pour calculer la position d'un récepteur. Afin de fournir ce service innovant, des techniques spécifiques d'estimation de pseudo-distance et d'identification d'émetteurs ont été développées dans le cadre de cette thèse. Le principal résultat de cette étude est d'avoir montré la faisabilité du positionnement utilisant un système DVB-SH, ne nécessitant que de légères modifications du système qui n'apportent aucune dégradation auservice de diffusion TV. De premières simulations ont montré une précision de positionnement autour de 40m en utilisant des mesures réalistes de canal de propagation urbain