iccv iccv2013 iccv2013-68 iccv2013-68-reference knowledge-graph by maker-knowledge-mining
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Author: Thomas Kuo, Santhoshkumar Sunderrajan, B.S. Manjunath
Abstract: This paper addresses the novel and challenging problem of aligning camera views that are unsynchronized by low and/or variable frame rates using object trajectories. Unlike existing trajectory-based alignment methods, our method does not require frame-to-frame synchronization. Instead, we propose using the intersections of corresponding object trajectories to match views. To find these intersections, we introduce a novel trajectory matching algorithm based on matching Spatio-Temporal Context Graphs (STCGs). These graphs represent the distances between trajectories in time and space within a view, and are matched to an STCG from another view to find the corresponding trajectories. To the best of our knowledge, this is one of the first attempts to align views that are unsynchronized with variable frame rates. The results on simulated and real-world datasets show trajectory intersections area viablefeatureforcamera alignment, and that the trajectory matching method performs well in real-world scenarios.