An integrated scheme for object-based video abstraction
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Multimedia Tools and Applications
Making a Long Video Short: Dynamic Video Synopsis
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Seam carving for content-aware image resizing
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Nonchronological Video Synopsis and Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video condensation by ribbon carving
IEEE Transactions on Image Processing
Summarizing high-level scene behavior
Machine Vision and Applications
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This paper presents a real time tunnel based video summarization using direct shift collision detection. The algorithm first detects objects from each video frame and segments them into slices using HOG object detection. Slices are then tracked as a tunnel which describes movement of objects in time space. We then propose direct shift collision detection algorithm (DSCD) to compute a distance for compacting tunnels. Shifting tunnels using DSCD yields the results of multiple activity tunnels appeared simultaneously while they are originally appeared at the different time. In order to solve such problem, our proposed film map generation technique is used to summarize a video which leaves just-in-time renderer to render only necessary frames. The combination of these three proposed methods reveal an overall performance that gives us real time results without losing the main contents of summarized video.