In this thesis the concept behind our notion of video sculpture is to imagine an image sequence or movie as a three dimensional volume. We then also imagine that there is a frameset that traverses the image sequence to give us what we commonly think of as a video or movie. In the ordinary sense this frameset moves through an image sequence in a completely timeparallel linear fashion. In video sculpture, we free the frameset from these bounds so that we can sample space and time in completely unorthodox ways. We can view the whenwhere in previously unforeseen perspectives. Slices of the video environment can simultaneously reveal both past and future actions within a single frame. Building on this free representation of video spacetime, we then wrest the frame once more from the present constraints of topography and/or topology. The frame can bend and twist and jump and dive. The view of a fading quadratic surface cutting through two scenes makes for a beautiful curtain transition. We present a framework and an implementation for modeling the frame as it passes through the image sequence volume object.

In this thesis we present an effective steganalysis technique for digital video sequences based on the collusion attack. Steganalysis is the process of detecting with a high probability the presence of covert data in multimedia. Existing algorithms for steganalysis target detecting covert information in still images. When applied directly to video sequences these approaches are suboptimal. In this thesis we present methods that overcome this limitation by using redundant information present in the temporal domain to detect covert messages in the form of Gaussian watermarks. In particular we target the spread spectrum steganography method because of its widespread use. Our gains are achieved by exploiting the collusion attack that has recently been studied in the field of digital video watermarking and more sophisticated pattern recognition tools. Through analysis and simulations we, evaluate the effectiveness of the video steganalysis method based on averaging based collusion scheme. Other forms of collusion attack in the form of weighted linear collusion and block-based collusion schemes have been proposed to improve the detection performance. The proposed steganalsyis methods were successful in detecting hidden watermarks bearing low SNR with high accuracy. The simulation results also show the improved performance of the proposed temporal based methods over the spatial methods. We conclude that the essence of future video steganalysis techniques lies in the exploitation of the temporal redundancy.

Thesis (Ph.D.)--Liberty University, 2009. / Includes bibliographical references.

Thesis (M. Phil.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 130-133).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 94-103).

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Vita. Includes bibliographical references (leaves 149-160). Also available in electronic version. Access restricted to campus users.

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references (leaves 63-68). Also available in electronic version. Access restricted to campus users.

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / Airborne videos are crucial for monitoring unmanned aircraft systems (UAS). However, the number of videos that could be sent to ground is limited due to the bandwidth of a telemetry system. An architecture of airborne video acquirement system with real-time management is present in this paper. In addition to acquire videos and other data like control commands, that architecture make it possible to manage and switch the videos to be transferred to the ground through telemetry channels for ground real-time monitoring and controlling.

People often have difficulties finding specific information in video because of its linear and unstructured nature. Segmenting long videos into small clips by topics and providing browsing and search functionalities is beneficial for information searching. However, manual segmentation is labor intensive and existing automated segmentation methods are not effective for plenty of amateur made and unedited lecture videos. The objectives of this dissertation are to develop 1) automated segmentation algorithms to extract the topic structure of a lecture video, and 2) retrieval algorithms to identify the relevant video segments for user queries.Based on an extensive literature review, existing segmentation features and approaches are summarized and research challenges and questions are presented. Manual segmentation studies are conducted to understand the content structure of a lecture video and a set of potential segmentation features and methods are extracted to facilitate the design of automated segmentation approaches. Two static algorithms are developed to segment a lecture video into a list of topics. Features from multimodalities and various knowledge sources (e.g. electronic slides) are used in the segmentation algorithms. A dynamic segmentation method is also developed to retrieve relevant video segments of appropriate sizes based on the questions asked by users. A series of evaluation studies are conducted and results are presented to demonstrate the effectiveness and usefulness of the automated segmentation approaches.

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