449 Papers
4.9K Citations
Zicheng Liu is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Computer science & Microphone. The author has an hindex of 60, co-authored 343 publications. Previous affiliations of Zicheng Liu include Microsoft & University of Illinois at Urbana–Champaign.
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Papers
Head-size equalization for better visual perception of video conferencing
Zicheng Liu,Michael F. Cohen +1 more
- 06 Jul 2005
TL;DR: This paper presents a novel technique, called spatially-varying-uniform scaling functions, to warp the images to equalize the head sizes of the meeting participants without causing undue distortion, and shows a specially designed five-lens camera to capture, stitch, and warp images in real time without sacrificing resolution.
Real-Time Gaze Estimation with Online Calibration
TL;DR: Unlike previous gaze estimation methods using explicit offline calibration with fixed number of calibration points or implicit calibration, the authors' approach constantly improves person-specific eye parameters through online calibration, which enables the system to adapt gradually to a new user.
38
Towards accurate and robust cross-ratio based gaze trackers through learning from simulation
Jia-Bin Huang,Qin Cai,Zicheng Liu,Narendra Ahuja,Zhengyou Zhang +4 more
- 26 Mar 2014
TL;DR: This paper introduces an adaptive homography mapping for achieving gaze prediction with higher accuracy at the calibration position and more robustness under head movements and shows that the method compares favorably against other state-of-the-art CR based methods.
37
Patent
Head pose tracking using a depth camera
Zicheng Liu,Zhengyou Zhang,Zhenning Li +2 more
- 14 Jan 2013
TL;DR: In this article, a head pose tracking technique is presented that uses a group of sensors configured so as to be disposed on a user's head to identify a current head pose location and orientation.
37
Image-to-Class Dynamic Time Warping for 3D hand gesture recognition
Hong Cheng,Zhongjun Dai,Zicheng Liu +2 more
- 15 Jul 2013
TL;DR: The main idea is that the time-series curve of a 3D hand gesture is divided into various finger combinations, called `fingerlets', which can either be learned or be set manually to represent each gesture and to capture inter-class variations.
37