Camera Alignment using Trajectory Intersections in Unsynchronized Videos


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 are a viable feature for camera alignment, and that the trajectory matching method performs well in real-world scenarios.

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Thomas Kuo, Santhoshkumar Sunderrajan, and B.S. Manjunath,
IEEE International Conference on Computer Vision, Sydney, Dec. 2013.
Node ID: 609 , DB ID: 419 , Lab: VRL , Target: Proceedings