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10 June 2024 ThumbTracks: a spatio-temporal assessment on SIFT variants in wide area motion imagery
Jaired Collins, Joshua Fraser, Deniz Kavzak Ufuktepe, Timothy Krock, Kannappan Palaniappan
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Proceedings Volume PC13037, Geospatial Informatics XIV; PC1303705 (2024) https://doi.org/10.1117/12.3029804
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States
Abstract
This study evaluates seven prominent SIFT implementations for feature detection in Wide Area Motion Imagery (WAMI): Lowe's archived code, VLFeat, OpenCV, SIFT anatomy, CudaSIFT, SiftGPU, and PopSift. We use spatio-temporal patch animations, termed ThumbTracks, to assess each method's performance in terms of jitter, wandering, and track switches. Additionally, we analyze the clustering of SIFT descriptors using t-distributed stochastic neighbor embeddings. Our results reveal significant variations in the performance of different SIFT variants, with implications for their suitability in various WAMI applications. We provide recommendations for selecting the most appropriate SIFT implementation based on feature stability, computational efficiency, and accuracy requirements.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Jaired Collins, Joshua Fraser, Deniz Kavzak Ufuktepe, Timothy Krock, and Kannappan Palaniappan "ThumbTracks: a spatio-temporal assessment on SIFT variants in wide area motion imagery", Proc. SPIE PC13037, Geospatial Informatics XIV, PC1303705 (10 June 2024); https://doi.org/10.1117/12.3029804
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KEYWORDS
Detection and tracking algorithms
Anatomy
Deep learning
Reliability
Stochastic processes
Switches
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