RECOGNITION OF FACES FROM SINGLE AND MULTI-VIEW VIDEOS

Face recognition has been an active research field for decades. In recent years, with videos playing an increasingly important role in our everyday life, video-based face recognition has begun to attract considerable research interest. This leads to a wide range of potential application areas, including TV/movies search and parsing, video surveillance, access control etc. Preliminary research results in this field have suggested that by exploiting the abundant spatial-temporal information contained in videos, we can greatly improve the accuracy and robustness of a visual recognition system. On the other hand, as this research area is still in its infancy, developing an end-to-end face processing pipeline that can robustly detect, track and recognize faces remains a challenging task. The goal of this dissertation is to study some of the related problems under different settings. We address the video-based face association problem, in which one attempts to extract face tracks of multiple subjects while maintaining label consistency. Traditional tracking algorithms have difficulty in handling this task, especially when challenging nuisance factors like motion blur, low resolution or significant camera motions are present. We demonstrate that contextual features, in addition to face appearance itself, play an important role in this case. We propose principled methods to combine multiple features using Conditional Random Fields and Max-Margin Markov networks to infer labels for the detected faces. Different from many existing approaches, our algorithms work in online mode and hence have a wider range of applications. We address issues such as parameter learning, inference and handling false positves/negatives that arise in the proposed approach. Finally, we evaluate our approach on several public databases. We next propose a novel video-based face recognition framework. We address the problem from two different aspects: To handle pose variations, we learn a Structural-SVM based detector which can simultaneously localize the face fiducial points and estimate the face pose. By adopting a different optimization criterion from existing algorithms, we are able to improve localization accuracy. To model other face variations, we use intra-personal/extra-personal dictionaries. The intra-personal/extra-personal modeling of human faces has been shown to work successfully in the Bayesian face recognition framework. It has additional advantages in scalability and generalization, which are of critical importance to real-world applications. Combining intra-personal/extra-personal models with dictionary learning enables us to achieve state-of-arts performance on unconstrained video data, even when the training data come from a different database. Finally, we present an approach for video-based face recognition using camera networks. The focus is on handling pose variations by applying the strength of the multi-view camera network. However, rather than taking the typical approach of modeling these variations, which eventually requires explicit knowledge about pose parameters, we rely on a pose-robust feature that eliminates the needs for pose estimation. The pose-robust feature is developed using the Spherical Harmonic (SH) representation theory. It is extracted using the surface texture map of a spherical model which approximates the subject's head. Feature vectors extracted from a video are modeled as an ensemble of instances of a probability distribution in the Reduced Kernel Hilbert Space (RKHS). The ensemble similarity measure in RKHS improves both robustness and accuracy of the recognition system. The proposed approach outperforms traditional algorithms on a multi-view video database collected using a camera network

A DECISION-THEORETIC APPROACH FOR CONTROLLING AND COORDINATING MULTIPLE ACTIVE CAMERAS IN SURVEILLANCE

Ph.DDOCTOR OF PHILOSOPH

Combat Identification Using Multiple TUAV Swarm

In modern warfare, Tactical Unmanned Aerial Vehicles (TUAVs) are rapidly taking on a leading role in traditional and non-traditional ISR, to include Automatic Target Recognition (ATR). However, additional advancements in processors and sensors on TUAVs are still needed before they can be widely employed as a primary source for positive identification in the Combat Identification (CID) process. Cost is a driving factor for operating an ATR system using multiple TUAVs. The cost of high quality sensors appropriate for a single TUAV can be significantly higher than less sophisticated sensors suitable for deployment on a group, or swarm, of coordinated TUAVs. Employing two or more coordinated TUAVs with less complex sensors may lead to an equivalent or even better CID call than sending a single TUAV with more sophisticated sensors at a significantly higher cost. In addition, the coordinated TUAVs may be capable of reducing the time needed to correctly discriminate an object. Five measures of performance (accuracy, number of TUAVs shot down, TUAV preparation time, mean of decision time, mean of simulated mission time) from the simulation models are collected to compare the swarm system to the single TUAV system. Statistical comparisons are conducted using a paired t-test. The results illustrate improved performance of our swarm systems across most measures of performance

Gesture Based Character Recognition

Gesture is rudimentary movements of a human body part, which depicting the important movement of an individual. It is high significance for designing efficient human-computer interface. An proposed method for Recognition of character(English alphabets) from gesture i.e gesture is performed by the utilization of a pointer having color tip (is red, green, or blue). The color tip is segment from back ground by converting RGB to HSI color model. Motion of color tip is identified by optical flow method. During formation of multiple gesture the unwanted lines are removed by optical flow method. The movement of tip is recoded by Motion History Image(MHI) method. After getting the complete gesture, then each character is extracted from hand written image by using the connected component and the features are extracted of the correspond character. The recognition is performed by minimum distance classifier method (Modified Hausdorf Distance). An audio format of each character is store in data-set so that during the classification, the corresponding audio of character will play

OPTIMIZATION OF FPGA-BASED PROCESSOR ARCHITECTURE FOR SOBEL EDGE DETECTION OPERATOR

This dissertation introduces an optimized processor architecture for Sobel edge detection operator on field programmable gate arrays (FPGAs). The processor is optimized by the use of several optimization techniques that aim to increase the processor throughput and reduce the processor logic utilization and memory usage. FPGAs offer high levels of parallelism which is exploited by the processor to implement the parallel process of edge detection in order to increase the processor throughput and reduce the logic utilization. To achieve this, the proposed processor consists of several Sobel instances that are able to produce multiple output pixels in parallel. This parallelism enables data reuse within the processor block. Moreover, the processor gains performance with a factor equal to the number of instances contained in the processor block. The processor that consists of one row of Sobel instances exploits data reuse within one image line in the calculations of the horizontal gradient. Data reuse within one and multiple image lines is enabled by using a processor with multiple rows of Sobel instances which allow the reuse of both the horizontal and vertical gradients. By the application of the optimization techniques, the proposed Sobel processor is able to meet real-time performance constraints due to its high throughput even with a considerably low clock frequency. In addition, logic utilization of the processor is low compared to other Sobel processors when implemented on ALTERA Cyclone II DE2-70

Proceedings of the International Micro Air Vehicles Conference and Flight Competition 2017 (IMAV 2017)

The IMAV 2017 conference has been held at ISAE-SUPAERO, Toulouse, France from Sept. 18 to Sept. 21, 2017. More than 250 participants coming from 30 different countries worldwide have presented their latest research activities in the field of drones. 38 papers have been presented during the conference including various topics such as Aerodynamics, Aeroacoustics, Propulsion, Autopilots, Sensors, Communication systems, Mission planning techniques, Artificial Intelligence, Human-machine cooperation as applied to drones

Narratives of ocular experience in interactive 360° environments

The purpose of this research project was to examine how immersive digital virtual technologies have the potential to expand the genre of interactive film into new forms of audience engagement and narrative production. Aside from addressing the limitations of interactive film, I have explored how interactive digital narratives can be reconfigured in the wake of immersive media. My contribution to knowledge stems from using a transdisciplinary synthesis of the interactive systems in film and digital media art, which is embodied in the research framework and theoretical focal point that I have titled Cynematics (chapter 2). Using a methodology that promotes iterative experimentation I developed a series of works that allowed me to practically explore the limitations of interactive film systems that involve non-haptic user interaction. This is evidenced in the following series of works: Virtual Embodiment, Narrative Maze, Eye Artefact Interactions and Routine Error - all of which are discussed in chapter 4 of this thesis. Each of these lab experiments collectively build towards the development of novel interactive 360° film practices. Funneling my research towards these underexplored processes I focused on virtual gaze interaction (chapters 4-6), aiming to define and historically contextualise this system of interaction, whilst critically engaging with it through my practice. It is here that gaze interaction is cemented as the key focus of this thesis. The potential of interactive 360° film is explored through the creation of three core pieces of practice, which are titled as follows: Systems of Seeing (chapter 5), Mimesis (chapter 6), Vanishing Point (chapter 7). Alongside the close readings in these chapters and the theoretical developments explored in each are the interaction designs included in the appendix of the thesis. These provide useful context for readers unable to experience these site-specific installations as virtual reality applications. After creating these systems, I established terms to theoretically unpack some of the processes occurring within them. These include Datascape Mediation (chapter 2), which frames agency as a complex entanglement built on the constantly evolving relationships between human and machine - and Live-Editing Practice (chapter 7), which aims to elucidate how the interactive 360° film practice designed for this research leads to new way of thinking about how we design, shoot and interact with 360° film. Reflecting on feedback from exhibiting Mimesis I decided to define and evaluate the key modes of virtual gaze interaction, which led to the development of a chapter and concept referred to as The Reticle Effect (chapter 6). This refers to how a visual overlay that is used to represent a user's line of sight not only shapes their experience of the work, but also dictates their perception of genre. To navigate this, I combined qualitative and quantitative analysis to explore user responses to four different types of gaze interaction. In preparing to collect this data I had to articulate these different types of interaction, which served to demarcate the difference between each of these types of gaze interaction. Stemming from this I used questionnaires, thematic analysis and data visualisation to explore the use and response to these systems. The results of this not only supports the idea of the reticle effect, but also gives insight into how these different types of virtual gaze interaction shape whether these works are viewed as games or as types of interactive film. The output of this allowed me to further expand on interactive 360° film as a genre of immersive media and move beyond the realm of interactive film into new technological discourses, which serves to validate the nascent, yet expansive reach of interactive 360° film as a form of practice. The thesis is concluded by framing this research within the wider discourse of posthuman theory as given that the technologies of immersive media perpetuate a state of extended human experience - how we interact and consider the theories that surround these mediums needs to be considered in the same way. The practice and theory developed throughout this thesis contribute to this discourse and allow for new ways of considering filmic language in the wake of interactive 360° film practice

Advanced Cosmic-Ray Composition Experiment for Space Station (ACCESS): ACCESS Accommodation Study Report

In 1994 NASA Administrator selected the first high-energy particle physics experiment for the Space Station, the Alpha Magnetic Spectrometer (AMS), to place a magnetic spectrometer in Earth orbit and search for cosmic antimatter. A natural consequence of this decision was that NASA would begin to explore cost-effective ways through which the design and implementation of AMS might benefit other promising payload experiments. The first such experiment to come forward was Advanced Cosmic-Ray Composition Experiment for Space Station (ACCESS) in 1996. It was proposed as a new mission concept in space physics to attach a cosmic-ray experiment of weight, volume, and geometry similar to the AMS on the International Space Station (ISS), and replace the latter as its successor when the AMS is returned to Earth. This was to be an extension of NASA's suborbital balloon program, with balloon payloads serving as the precursor flights and heritage for ACCESS. The balloon programs have always been a cost-effective NASA resource since the particle physics instrumentation for balloon and space applications are directly related. The next step was to expand the process, pooling together expertise from various NASA centers and universities while opening up definition of the ACCESS science goals to the international community through the standard practice of peer review. This process is still ongoing, and the accommodation study presented here will discuss the baseline definition of ACCESS as we understand it today

Research and technology

Significant research and technology activities at the Johnson Space Center (JSC) during Fiscal Year 1990 are reviewed. Research in human factors engineering, the Space Shuttle, the Space Station Freedom, space exploration and related topics are covered

Improved nonlinear filtering for target tracking.

The objective of this research is to develop robust and accurate tracking algorithms for various tracking applications. These tracking problems can be formulated as nonlinear filtering problems. The tracking algorithms will be developed based on an emerging promising nonlinear filter technique, known as sequential importance sampling (nick-name: particle filtering). This technique was introduced to the engineering community in the early years of 2000, and it has recently drawn significant attention from engineers and researchers in a wide range of areas. Despite the encouraging results reported in the current literature, there are still many open questions to be answered. For the first time, the major research effort will be focusing on making improvement to the particle filter based tracking algorithm in the following three aspects: (I) refining the particle filtering process by designing better proposal distributions (II) refining the dynamic model by using multiple-model method, (i.e. using switching dynamics and jump Markov process) and (III) refining system measurements by incorporating a data fusion stage for multiple measurement cues