Optimizing Multiple Object Tracking and Best View Video Synthesis

被引:26
作者
Jiang, Hao [1 ]
Fels, Sidney [2 ]
Little, James J.
机构
[1] Boston Coll, Dept Comp Sci, Chestnut Hill, MA 02467 USA
[2] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC V6T 1Z4, Canada
关键词
Dynamic programming; linear programming; multiple object tracking; video synthesis;
D O I
10.1109/TMM.2008.2001379
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:997 / 1012
页数:16
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