Optimizing Multiple Object Tracking and Best View Video Synthesis

TitleOptimizing Multiple Object Tracking and Best View Video Synthesis
Publication TypeJournal Article
Year of Publication2008
AuthorsJiang, H., S. Fels, and J. J. Little
JournalIEEE Transactions on Multimedia

We study schemes to tackle problems of optimizing multiple object tracking and best-view video synthesis. A novel linear relaxation method is proposed for the class of multiple object tracking problems where the inter-object interaction metric is convex and the intra-object term quantifying object state continuity may use any metric. This scheme models object tracking as multi-path searching. It explicitly models track interaction, such as object spatial layout consistency or mutual occlusion, and optimizes multiple object tracks simultaneously. The proposed scheme does not rely on track initialization and complex heuristics. It has much less average complexity than previous efficient exhaustive search methods such as extended dynamic programming and can find the global optimum with high probability. Given the tracking data from our method, optimizing best-view video synthesis using multiple-view videos is further studied, which is formulated as a recursive decision problem and optimized by a dynamic programming approach. The proposed object tracking and best-view synthesis methods have found successful applications in My View-a system to enhance media content presentation of multiple-view video.


a place of mind, The University of British Columbia

Electrical and Computer Engineering
2332 Main Mall
Vancouver, BC Canada V6T 1Z4
Tel +1.604.822.2872
Fax +1.604.822.5949

Emergency Procedures | Accessibility | Contact UBC | © Copyright 2020 The University of British Columbia