Distance transformations in digital images
Computer Vision, Graphics, and Image Processing
Finding Trajectories of Feature Points in a Monocular Image Sequence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion recovery for video content classification
ACM Transactions on Information Systems (TOIS) - Special issue on video information retrieval
Computer Vision
Motion-Location Based Indexing Method for Retrieving MPEG Videos
DEXA '98 Proceedings of the 9th International Workshop on Database and Expert Systems Applications
Models for motion-based video indexing and retrieval
IEEE Transactions on Image Processing
A fully automated content-based video search engine supporting spatiotemporal queries
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, efficient algorithms for content-based video retrieval using motion information are proposed. We describe algorithms for a temporal scale invariant and spatial translation absolute retrieval using trail model and a temporal scale absolute and spatial translation invariant retrieval using trajectory model. In the retrieval using trail model, the Distance transformation is performed on each trail image in database. Then, from a given query trail the pixel values along the query trail are added in each distance image to compute the average distance between the trails of query image and database image. For the spatial translation invariant retrieval using trajectory model, a new coding scheme referred to as Motion Retrieval Code is proposed, which is suitable for representing object motions in video. Since the Motion Retrieval Code is designed to reflect the human visual system, it is very efficient to compute the similarity between two motion vectors, using a few bit operations.