Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Spatio-Temporal Alignment of Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
View-invariant Alignment and Matching of Video Sequences
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
ACM SIGGRAPH 2004 Papers
Wide Baseline Matching between Unsynchronized Video Sequences
International Journal of Computer Vision
Introduction to Information Retrieval
Introduction to Information Retrieval
Parametric Image Alignment Using Enhanced Correlation Coefficient Maximization
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIFT Flow: Dense Correspondence across Different Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Efficient Visual Search of Videos Cast as Text Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Alignment for Change Detection
IEEE Transactions on Image Processing
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This paper addresses the problem of aligning two unsynchronized video sequences. We present a novel approach that allows for temporal and spatial alignment of similar videos captured from independently moving cameras. The goal is to synchronize two videos of a scene such that changes between the videos can be detected automatically. This aims at applications in driver assistance or surveillance systems but we also envision applications in map building. Our approach is novel in that it adapts an efficient information retrieval framework to a computer vision problem. In addition, we extend the recent ECC image-alignment algorithm to the temporal dimension in order to improve spatial registration and enable synchro refinement. Experiments with traffic videos recorded by in-vehicle cameras demonstrate the efficiency of the proposed method and verify its effectiveness with respect to spatio-temporal alignment accuracy.