Transcoding Surveillance Video (TSV) dataset is the first well-marked dataset for evaluating the affect of video transcoding parameters on the performance of visual object tracking algorithms. the proposed TSV dataset contains 3840 transcoding surveillance videos that have been used to evaluate ten object tracking methods.
References :
[UAV] M. Mueller, N. Smith, B. Ghanem, A benchmark and simulator for uav tracking, in: European conference on computer vision, Springer, 2016, pp. 445–461.
[NfS] H. Kiani Galoogahi, A. Fagg, C. Huang, D. Ramanan, S. Lucey, Need for speed: A benchmark for higher frame rate object tracking, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 1125–1134.
[VOT2019] M. Kristan, J. Matas, A. Leonardis, M. Felsberg, R. Pflugfelder, J. Kamarainen, L. Cehovin Zajc, O. Drbohlav, A. Lukezic, A. Berg, et al., The seventh visual object tracking vot2019 challenge results, in: Proceedings of the IEEE International Conference on Computer Vision Workshops, 2019, pp. 0–0.
[LaSOT] H. Fan, al., Lasot: A high-quality benchmark for large-scale single object tracking, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019, pp. 5374–5383.
If you have any questions about the project, please feel free to contact authors: Taieb Chachou (taieb.chachou[at]gmail.com), Sid Ahmed Fezza (sfezza[at]ensttic.dz), Wassim Hamidouche (whamidouche[at]gmail.com), Ghalem Belalem (ghalem1dz[at]gmail.com).