A Survey on Gait Recognition
ACM Computing Surveys2018Vol. 51(5), pp. 1–35
Citations Over TimeTop 1% of 2018 papers
Changsheng Wan, Li Wang, Vir V. 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Fua, Liang Wang, Huazhong Ning, Tieniu Tan, Weiming Hu, Ju Man, Bir Bhanu, Jianyi Liu, Nanning Zheng, J Heikki, Ailisto, Marja Satu, Makela, K Nakajima, Y Mizukami, K Tanaka, T Tamura, Michael Otero, Lily Lee, W, Eric Grimson, N Peter, Joo Belhumeur, David Hespanha, Kriegman, Aravind Sundaresan, Amit Roychowdhury, Rama Chellappa, K Khoshelham, A Schmitz, M Ye, R Shapiro, R Yang, B Noehren, B Dikovski, G Madjarov, D Gjorgjevikj, Aaron Staranowicz, Garrett Brown, Gian Mariottini, Chewyean Yam, Mark Nixon, John Carter, Shiloh Dockstader, Michel Berg, A Tekalp, Jianzhong Liu Rong, Zhou, Ming Liu, Xiangfeng Hou, Thang Hoang, Davrondzhon Gafurov, Kirsi Helkala, Torkjel Sndrol, Mohammad Derawi, Patrick Bours, Davrondzhon Gafurov, Einar Snekkenes, Patrick Bours, D Gafurov, K Helkala, T Soendrol, Jam Jenkins, Carla Ellis, Lee Middleton, Alex Buss, Alex Bazin, Mark Nixon, Robert Orr, Gregory Abowd, Jaakko Suutala, Juha Rning, J Suutala, J Roning, Jaakko Suutala, Juha Roning, Yazhou Wang, Aly Fathy, Dave Tahmoush, Jerry Silvious, Richard Seely, Sina Samangooei, Middleton Lee, John Carter, Mark Nixon, Sungjun Hong, Heesung Lee, Kyongsae Oh, Mignon Park, Euntail Kim, Yuan Wang, Shiqi Yu, Yunhong Wang, Tieniu Tan, Liang Wang, Tieniu Tan, Weiming Hu, Huazhong Ning, Alex Bazin, Bufu Huang, Meng Chen, Panfeng Huang, Yangsheng Xu, J Mantyjarvi, M Lindholm, E Vildjiounaite, S Makela, L Rong, D Zhiguo, Z Jianzhong, L Ming, Elena Vildjiounaite, Mikko Lindholm, Heikki Ailisto, Muhammad Muaaz, Mohammad Derawi, Patrick Bours, Kjetil Holien, D Gafurov, E Snekkenes, P Bours, Claudia Nickel, Mohammad Derawi, Patrick Bours, Christoph Busch, Hee Jang, Doosung Yoo, Ki Hwang, Mark Moon, Nixon, V Nikolaos, Zhiwei Boulgouris, Chi, Xuelong Li, Stephen Maybank, Shuicheng Yan, Dacheng Tao, Dong Xu, Aaron Bobick, Amos Johnson, R Tanawongsuwan, A Bobick, David Cunado, Mark Nixon, John Carter, Jason Nash, John Carter, Mark Nixon, Shuai Zheng, Junge Zhang, Kaiqi Huang, Ran He, Tieniu Tan, S Sarkar, P 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Yagi, Shiqi Yu, Tieniu Tan, Kaiqi Huang, Kui Jia, Xinyu Wu, Zhaojun Xue, Dong Ming, Wei Song, Baikun Wan, Shijiu Jin, Jiwen Lu, Yap Peng, Tan, Xin Geng, Liang Wang, Ming Li, Qiang Wu, Kate Smithmiles, Davrondzhon Gafurov, Einar Snekkenes, Patrick Bours
Abstract
Recognizing people by their gait has become more and more popular nowadays due to the following reasons. First, gait recognition can work well remotely. Second, gait recognition can be done from low-resolution videos and with simple instrumentation. Third, gait recognition can be done without the cooperation of individuals. Fourth, gait recognition can work well while other features such as faces and fingerprints are hidden. Finally, gait features are typically difficult to be impersonated. Recent ubiquity of smartphones that capture gait patterns through accelerometers and gyroscope and advances in machine learning have opened new research directions and applications in gait recognition. A timely survey that addresses current advances is missing. In this article, we survey research works in gait recognition. In addition to recognition based on video, we address new modalities, such as recognition based on floor sensors, radars, and accelerometers; new approaches that include machine learning methods; and examine challenges and vulnerabilities in this field. In addition, we propose a set of future research directions. Our review reveals the current state-of-art and can be helpful to both experts and newcomers of gait recognition. Moreover, it lists future works and publicly available databases in gait recognition for researchers.
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