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Full-Text Articles in Computer Engineering
Motion Retrieval By Temporal Slices Analysis, Chong-Wah Ngo, Chong-Wah Ngo, Hong-Jiang Zhang
Motion Retrieval By Temporal Slices Analysis, Chong-Wah Ngo, Chong-Wah Ngo, Hong-Jiang Zhang
Research Collection School Of Computing and Information Systems
In this papel; we investigate video shots retrieval based on the analysis of temporal slice images. Temporal slices are a set of2D images extracted along the time dimension of image sequences. They encode rich set of motion clues for shot similarity measure. Because motion is depicted as texture orientation in temporal slices, we utilize various texture features such as tensor histogram, Gabor feature, and the statistical feature of co-occurrence matrix extracted directly from slices for motion description and retrieval. In this way, motion retrieval can be treated in a similar way as texture retrieval problem. Experimental results indicate that the …
On Clustering And Retrieval Of Video Shots Through Temporal Slices Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang
On Clustering And Retrieval Of Video Shots Through Temporal Slices Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang
Research Collection School Of Computing and Information Systems
Based on the analysis of temporal slices, we propose novel approaches for clustering and retrieval of video shots. Temporal slices are a set of two-dimensional (2-D) images extracted along the time dimension of an image volume. They encode rich set of visual patterns for similarity measure. In this paper, we first demonstrate that tensor histogram features extracted from temporal slices are suitable for motion retrieval. Subsequently, we integrate both tensor and color histograms for constructing a two-level hierarchical clustering structure. Each cluster in the top level contains shots with similar color while each cluster in bottom level consists of shots …
A Lessons Learned Repository For Computer Forensics, Warren Harrison, George Heuston, Mark Morrissey, David Aucsmith, Sarah Mocas, Steve Russelle
A Lessons Learned Repository For Computer Forensics, Warren Harrison, George Heuston, Mark Morrissey, David Aucsmith, Sarah Mocas, Steve Russelle
Computer Science Faculty Publications and Presentations
The Law Enforcement community possesses a large, but informal, community memory with respect to digital forensics. Large, because the experiences of every forensics technician and investigator contribute to the whole. Informal because there is seldom an explicit mechanism for disseminating this wisdom except “over the water cooler”. As a consequence, the same problems and mistakes continue to resurface and the same solutions are re-invented. In order to better exploit this informal collection of wisdom, the key points of each experience can be placed into a Repository for later dissemination. We describe a web-based Lessons Learned Repository (LLR) that facilitates contribution …