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The amount of digital video has been increasing dramatically due to the technology advances in video capturing, storage, and compression. The usefulness of vast repositories of digital information is limited by the effectiveness of the access methods, as shown by the Web explosion. The key issues in addressing the access methods are those of content description and of information space navigation. While textual documents in digital form are somewhat self-describing (i.e., they provide explicit indices, such as words and sentences that can be directly used to categorise and access them), digital video does not provide such an explicit content description. In order to access video material in an effective way, without looking at the material in its entirety, it is therefore necessary to analyse and annotate video sequences, and provide an explicit content description targeted to the user needs. Digital video is a very rich medium, and the characteristics in which users may be interested are quite diverse, ranging from the structure of the video to the identity of the people who appear in it, their movements and dialogues and the accompanying music and audio effects. Indexing digital video, based on its content, can be carried out at several levels of abstraction, beginning with indices like the video program name and name of subject, to much lower level aspects of video like the location of edits and motion properties of video. Manual video indexing requires the sequential examination of the entire video clip. This is a time-consuming, subjective, and expensive process. As a result, there is an urgent need for tools to automate the indexing process. In response to such needs, various video analysis techniques from the research fields of image processing and computer vision have been proposed to parse, index and annotate the massive amount of digital video data. However, most of these video analysis techniques have been developed for uncompressed video. Since most video data are stored in compressed formats for efficiency of storage and transmission, it is necessary to perform decompression on compressed video before such analysis techniques can be applied. Two consequences of having to first decompress before processing are incurring computation time for decompression and requiring extra auxiliary storage.To save on the computational cost of decompression and lower the overall size of the data which must be processed, this study attempts to make use of features available in compressed video data and proposes several video processing techniques operating directly on compressed video data. Specifically, techniques of processing MPEG-1 and MPEG-2 compressed data have been developed to help automate the video indexing process. This includes the tasks of video segmentation (shot boundary detection), camera motion characterisation, and highlights extraction (detection of skin-colour regions, text regions, moving objects and replays) in MPEG compressed video sequences. The approach of performing analysis on the compressed data has the advantages of dealing with a much reduced data size and is therefore suitable for computationally-intensive low-level operations. Experimental results show that most analysis tasks for video indexing can be carried out efficiently in the compressed domain. Once intermediate results, which are dramatically reduced in size, are obtained from the compressed domain analysis, partial decompression can be applied to enable high resolution processing to extract high level semantic information.

Zhang, Qian. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 97-111). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Information, products and services can be requested and purchased via the Interactive Video Data Service (IVDS) system developed by The Center for Wireless Telecommunications, Virginia Tech. This system consists of three components - User control, Repeater unit and a Host program. The user requests a service using his/her television remote (User control). A transceiver (User control) located near the television set responds to user requests by extracting information hidden in the commercial's audio, and transmitting information to the repeater unit. The receiver unit decodes received messages and forwards them in capsules to the Host component. Thus the user requests are received by the host system. The repeater unit is a real-time operating system with its in-built hardware and software functions. Application specific software can be written using the existing software drivers and libraries (kernel) to decode and process messages. The Host program monitors and responds to received user messages. This thesis focuses on the repeater unit hardware setup and discusses the application software implementation developed to receive messages from the transceiver box and to retransmit the messages in a different format over the Internet. The software specifications included no incoming message loss, ability to statically hold 10000 user messages, time-stamp and location-stamp (using a GPS receiver) forwarded messages, scheduling messages for retransmission based on message priority, and retransmission using the point-to-point protocol (PPP) using a dial-up modem connection. In order to achieve better performance the existing software kernel was re-written in some sections. This thesis also discusses some of the system limitations from the repeater unit's perspective. / Master of Science

This thesis will explore how customers and bartenders accomplish the service encounter in a public house, or bar. Whilst there is a body of existing literature on service encounters, this mainly investigates customer satisfaction and ignores the mundane activities that comprise the service encounter itself. In an attempt to fill this gap, I will examine how the activities unfold sequentially by examining the spoken and embodied conduct of the participants, over the course of the encounter. The data comprise audio -and video- recorded, dyadic and multi-party interactions between customer(s) and bartender(s), occurring at the bar counter. The data were analyzed using conversation analysis (CA) to investigate the talk and embodied conduct of participants, as these unfold sequentially. The first analytic chapter investigates how interactions between customers and bartenders are opened. The analysis reveals practices for communicating availability to enter into a service encounter; with customers being found to do this primarily through embodied conduct, and bartenders primarily through spoken turns. The second analytic chapter investigates the role of objects in the ordering sequence. Specifically, the analysis reveals how the Cash Till and the seating tables in the bar are mobilized by participants to accomplish action. In the third analytic chapter, multi-party interactions are investigated, focusing on the organization of turn-taking when two or more customers interact with one or more bartenders. Here, customers are found to engage in activities where they align as a unit, with a lead speaker, who interacts with the bartender on behalf of the party. In the final analytic chapter, the payment sequence of the service encounter is explored to investigate at what sequential position in the interaction payment, as an action, is oriented to. Analysis reveals that a wallet, purse, or bag, may be displayed and money or a payment card retrieved, in a variety of sequential slots, with each contributing differentially to the efficiency of the interaction. I also find that payment may be prematurely proffered due to the preference for efficiency. Overall, the thesis makes innovative contributions to our understanding of customer and bartender practices for accomplishing core activities in what members come to recognize as a service encounter It also contributes substantially to basic conversation analytic research on openings , which has traditionally been founded on telephone interactions, as well as the action of requesting. I enhance our knowledge of face-to-face opening practices, by revealing that the canonical opening sequence (see Schegloff, 1968; 1979; 1986) is not present, at least in this context. From the findings, I also develop our understanding of how objects constrain, or further, progressivity in interaction; while arguing for the importance of analysing the participants semiotic field in aggregate with talk and embodied conduct. The thesis also contributes to existing literature on multi-party interactions, identifying a new turn-taking practice with a directional flow that works effectively to accomplish ordering. Finally, I contribute to knowledge on the provision of payment, an under-researched yet prominent action in the service encounter. This thesis will show the applicability of CA to service providers; by analysing the talk and embodied conduct in aggregate, effective practices for accomplishing a successful service encounter are revealed.

In a world of ever increasing amounts of video data, we are forced to abandon traditional methods of scene interpretation by fully manual means. Under such circumstances, some form of automation is highly desirable but this can be a very open ended issue with high complexity. Dealing with such large amounts of data is a non-trivial task that requires efficient selective extraction of parts of a scene which have the potential to develop a higher semantic meaning, alone, or in combination with others. In particular, the types of video data that are in need of automated analysis tend to be outdoor scenes with high levels of activity generated from either foreground or background. Such dynamic scenes add considerable complexity to the problem since we cannot rely on motion energy alone to detect regions of interest. Furthermore, the behaviour of these regions of motion can differ greatly, while still being highly dependent, both spatially and temporally on the movement of other objects within the scene. Modelling these dependencies, whilst eliminating as much redundancy from the feature extraction process as possible are the challenges addressed by this thesis. In the first half, finding the right mechanism to extract and represent meaningful features from dynamic scenes with no prior knowledge is investigated. Meaningful or salient information is treated as the parts of a scene that stand out or seem unusual or interesting to us. The novelty of the work is that it is able to select salient scales in both space and time in which a particular spatio-temporal volume is considered interesting relative to the rest of the scene. By quantifying the temporal saliency values of regions of motion, it is possible to consider their importance in terms of both the long and short-term. Variations in entropy over spatio-temporal scales are used to select a context dependent measure of the local scene dynamics. A method of quantifying temporal saliency is devised based on the variation of the entropy of the intensity distribution in a spatio-temporal volume over incraeasing scales. Entropy is used over traditional filter methods since the stability or predictability of the intensity distribution over scales of a local spatio-temporal region can be defined more robustly relative to the context of its neighbourhood, even for regions exhibiting high intensity variation due to being extremely textured. Results show that it is possible to extract both locally salient features as well as globally salient temporal features from contrasting scenerios. In the second part of the thesis, focus will shift towards binding these spatio-temporally salient features together so that some semantic meaning can be inferred from their interaction. Interaction in this sense, refers to any form of temporally correlated behaviour between any salient regions of motion in a scene. Feature binding as a mechanism for interactive behaviour understanding is particularly important if we consider that regions of interest may not be treated as particularly significant individually, but represent much more semantically when considered in combination. Temporally correlated behaviour is identified and classified using accumulated co-occurrences of salient features at two levels. Firstly, co-occurrences are accumulated for spatio-temporally proximate salient features to form a local representation. Then, at the next level, the co-occurrence of these locally spatio-temporally bound features are accumulated again in order to discover unusual behaviour in the scene. The novelty of this work is that there are no assumptions made about whether interacting regions should be spatially proximate. Furthermore, no prior knowledge of the scene topology is used. Results show that it is possible to detect unusual interactions between regions of motion, which can visually infer higher levels of semantics. In the final part of the thesis, a more specific investigation of human behaviour is addressed through classification and detection of interactions between 2 human subjects. Here, further modifications are made to the feature extraction process in order to quantify the spatiotemporal saliency of a region of motion. These features are then grouped to find the people in the scene. Then, a loose pose distribution model is extracted for each person for finding salient correlations between poses of two interacting people using canonical correlation analysis. These canonical factors can be formed into trajectories and used for classification. Levenshtein distance is then used to categorise the features. The novelty of the work is that the interactions do not have to be spatially connected or proximate for them to be recognised. Furthermore, the data used is outdoors and cluttered with non-stationary background. Results show that co-occurrence techniques have the potential to provide a more generalised, compact, and meaningful representation of dynamic interactive scene behaviour.

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Traditional database systems only support textual and numerical data. Video data stored in these database systems can only be retrieved through their video identifiers, titles or descriptions. In the video data, frame-by-frame object change is one of the most obvious information. Each video contains temporal and spatial relationships between content objects. The temporal relationships can be specified between frame sequences and the spatial relationships can be specified by the relationships between objects in a single frame. The difficulty in designing a content-based video database system is how to store and describe the relationships between moving objects completely. Many researches on content-based video retrieval represented the content of video as a set of frames, but they either left out the temporal ordering of frames in the shot or only stored the relationships between objects in a single frame. According to these observations, we conclude that a content-based video database system requires video indexing, query processing and a convenient user interface to fit the requirements and characteristics of videos. In this thesis, we design and implement a query processing strategy for video data. In the proposed strategy, we consider three query types: the exact object match, the spatial-temporal object retrieval and the motion query, where a exact object match is to find the video files which contain the specific objects, a spatial-temporal objects retrieval is to retrieve the object pairs that satisfy some spatial-temporal relationships and a motion query is to find the set of frames which contain the object movements. Moreover, we consider three design issues: the video indexing, the video query processing and the video query interface. When there are a large number of videos in a video database and each video contains many shots, frames and objects, the processing time for content retrieval is tremendous. Thus, we need a proper video indexing strategy to speed up the searching time. In order to fulfill the spatial-temporal relationships of objects between different frames, we give the indexes both in the spatial and temporal axes. In the temporal index file structure, we propose the shot-based B+-tree to index the temporal data. In the spatial index file structure, we use R-tree to store not only the relationships between objects in one frame, but also the relationships of one object when the object first and last appears in the shot. Based on this strategy, we can describe the status of a moving object in details. For the part of query processing, we propose a signature file structure to filter out the videos that absolutely can not be the answer. After that, in order to determine whether the answer exists in the candidate videos, we use a multi-dimensional string, called binary string, to represent the spatial-temporal relationships between objects. Then, the video query processing problem will become a binary string matching problem. Finally, we design and implement an user-friendly user interface. Our system is performed on a Pentium III machine with one CPU clock rate of 550 MHz, 256 MB of main memory, running under Windows 2000 Professional edition, used Access 2000 database and coded in Delphi 6 with about 10,000 lines. From our experience, we show that the proposed system can support an efficient query processing, a fast searching capabilities and an user-friendly user interface.

An IVDS (Interactive Video Data Service) uses an interactive television system to transmit data to and from subscribers' homes. IVDS allows the viewer to interact with content provided on the television using a remote control. A typical IVDS application would be ordering an advertised product or playing along with a quiz show. The Virginia Tech Center for Wireless Telecommunications (CWT), under a contract with Interactive Return Service, Inc., is developing an IVDS system in which content is provided through the television cable system in the form of audio codes. A special remote control can detected these audio codes and query the user for input. The return path for this system is a wireless channel. The remote control contains a spread spectrum transmitter that transmits packets to a Repeater unit residing within a quarter mile of the user's home. With the popularity of the World Wide Web soaring, many companies are announcing internet appliances that will bring the content of the web to the user at a fraction of the cost of a standard personal computer. CWT has been contracted to extend the core IVDS system to provide a web browsing capability, allowing the user to browse the web with only the remote control. This thesis outlines the requirements of the IVDS Web Browser System. The different hardware design concepts are documented. The final Browser System specification is presented, as well as a board-level description of the Decoder Unit that is part of this final Browser System. Finally, a detailed description, current status, and simulation results are presented for the FPGA (Field Programmable Gate Array) that serves as the controller for the Decoder Unit. / Master of Science

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