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职业迁徙
个人简介
My research focuses on designing machines that measure, decode, and learn the deeper meaning
of human behaviors by exploiting the in-situ measurements of wearable cameras. A simple usage of
the wearable cameras does not solve behavioral understanding problems due to the first person biases
such as camera placement, anthropometric configurations, and physical/social interactions. Therefore,
representing human behaviors via first person perception is challenging, and I address this challenge
through the following three ingredients:
• Joint attention To understand social behaviors, e.g., social formations, in a form of joint attention,
or social saliency (Figure 1(a)) [1, 2, 3, 4].
• Physical sensation To predict one’s behaviors by decoding first person sensation into physical
quantities such as force, momentum, and energy (Figure 1(b)) [5, 6, 7].
• Social signal To recognize the meaning of human behaviors, e.g., social signals, by reconstructing
their activities in 3D (Figure 1(c)) [8, 9, 10, 11, 12].
In my Ph.D. and postdoctoral research, I have demonstrated the validity of my representation through
video editing [3], sport analytics [4], performance capture [12], and behavior prediction [1, 2, 6]. Research
projects have been featured in major media including IEEE Spectrum, NBC News, Discovery
News, and Wired, and I have co-organized a tutorial based on my thesis [13], “Group Behavior Analysis
and Its Applications1
” in conjunction with CVPR 2015.
研究兴趣
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Zhixuan Yu,Ziqian Bai,Abhimitra Meka,Feitong Tan, Qiangeng Xu, Rohit Pandey, Sean Fanello,Hyun Soo Park,Yinda Zhang
arxiv(2024)
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CVPR 2023 (2023): 4627-4636
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