Performance Evaluation Methodology for Long-Term Visual Object Tracking

Autor: Lukežič, Alan, Zajc, Luka Čehovin, Vojíř, Tomáš, Matas, Jiří, Kristan, Matej

A long-term visual object tracking performance evaluation methodology and a benchmark are proposed. Performance measures are designed by following a long-term tracking definition to maximize the analysis probing strength. The new measures outperform

Externí odkaz: http://arxiv.org/abs/1906.08675

FuCoLoT -- A Fully-Correlational Long-Term Tracker

Autor: Lukežič, Alan, Zajc, Luka Čehovin, Vojíř, Tomáš, Matas, Jiří, Kristan, Matej

We propose FuCoLoT -- a Fully Correlational Long-term Tracker. It exploits the novel DCF constrained filter learning method to design a detector that is able to re-detect the target in the whole image efficiently. FuCoLoT maintains several correlatio

Externí odkaz: http://arxiv.org/abs/1711.09594

Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking

Autor: Zajc, Luka Čehovin, Lukežič, Alan, Leonardis, Aleš, Kristan, Matej

Object-to-camera motion produces a variety of apparent motion patterns that significantly affect performance of short-term visual trackers. Despite being crucial for designing robust trackers, their influence is poorly explored in standard benchmarks

Externí odkaz: http://arxiv.org/abs/1612.00089

The Tenth Visual Object Tracking VOT2022 Challenge Results

Autor: Kristan, Matej, Leonardis, Aleš, Matas, Jiří, Felsberg, Michael, Pflugfelder, Roman, Kämäräinen, Joni-Kristian, Chang, Hyung Jin, Danelljan, Martin, Zajc, Luka Čehovin, Lukežič, Alan, Drbohlav, Ondrej, Björklund, Johanna, Zhang, Yushan, Zhang, Zhongqun, Yan, Song, Yang, Wenyan, Cai, Dingding, Mayer, Christoph, Fernández, Gustavo, Ben, Kang, Bhat, Goutam, Chang, Hong, Chen, Guangqi, Chen, Jiaye, Chen, Shengyong, Chen, Xilin, Chen, Xin, Chen, Xiuyi, Chen, Yiwei, Chen, Yu-Hsi, Chen, Zhixing, Cheng, Yangming, Ciaramella, Angelo, Cui, Yutao, Džubur, Benjamin, Dasari, Mohana Murali, Deng, Qili, Dhar, Debajyoti, Shangzhe, Di, Nardo, Emanuel Di, Daniel K., Du, Dunnhofer, Matteo, Fan, Heng, Feng, Zhenhua, Zhihong, Fu, Gao, Shang, Gorthi, Rama Krishna, Granger, Eric, Q. H., Gu, Gupta, Himanshu, Jianfeng, He, Keji, He, Huang, Yan, Jangid, Deepak, Rongrong, Ji, Jiang, Cheng, Jiang, Yingjie, Lawin, Felix Järemo, Kang, Ze, Kiran, Madhu, Kittler, Josef, Lai, Simiao, Lan, Xiangyuan, Lee, Dongwook, Lee, Hyunjeong, Lee, Seohyung, Hui, Li, Ming, Li, Wangkai, Li, Xi, Li, Xianxian, Li, Xiao, Li, Zhe, Li, Lin, Liting, Ling, Haibin, Liu, Bo, Liu, Chang, Liu, Si, Huchuan, Lu, Cruz, Rafael M. O., Bingpeng, Ma, Chao, Ma, Jie, Ma, Yinchao, Ma, Martinel, Niki, Memarmoghadam, Alireza, Micheloni, Christian, Moallem, Payman, Nguyen-Meidine, Le Thanh, Pan, Siyang, Park, Changbeom, Paudel, Danda, Paul, Matthieu, Peng, Houwen, Robinson, Andreas, Rout, Litu, Shan, Shiguang, Simonato, Kristian, Song, Tianhui, Song, Xiaoning, Sun, Chao, Sun, Jingna, Tang, Zhangyong, Timofte, Radu, Tsai, Chi-Yi, Gool, Luc Van, Verma, Om Prakash, Wang, Dong, Wang, Fei, Wang, Liang, Wang, Liangliang, Wang, Lijun, Wang, Limin, Wang, Qiang, Gangshan, Wu, Jinlin, Wu, Xiaojun, Wu, Xie, Fei, Tianyang, Xu, Wei, Xu, Yong, Xu, Yuanyou, Xu, Xue, Wanli, Xun, Zizheng, Yan, Bin, Yang, Dawei, Yang, Jinyu, Yang, Wankou, Yang, Xiaoyun, Yang, Yi, Yang, Yichun, Yang, Zongxin, Botao, Ye, Fisher, Yu, Hongyuan, Yu, Jiaqian, Yu, Qianjin, Yu, Weichen, Yu, Zhai, Jiang, Zhang, Chengwei, Zhang, Chunhu, Zhang, Kaihua, Zhang, Tianzhu, Zhang, Wenkang, Zhang, Zhibin, Zhang, Zhipeng, Zhao, Jie, Zhao, Shaochuan, Zheng, Feng, Zheng, Haixia, Zheng, Min, Zhong, Bineng, Zhu, Jiawen, Zhu, Xuefeng, Zhuang, Yueting

Publikováno v: Lecture Notes in Computer Science ISBN: 9783031250842

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d0500efd15806c5fc973651cf2ffe77
https://doi.org/10.1007/978-3-031-25085-9_25

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