Motion analysis of articulated objects from monocular images
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Updated: Aug 9, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
Published on: April 21, 2023
Xiaoyun Zhang1, Yuncai Liu, Thomas S Huang
1Institute of Image Processing and Pattern Recognition, Department of Automation, Shanghai Jiao Tong University at Min Hang Campus, 1954 Huashan Road, Min Hang District, Shanghai 200240, The Peoples Republic of China. xiao_yun@sjtu.org
Abstract:
This paper presents a new method of motion analysis of articulated objects from feature point correspondences over monocular perspective images without imposing any constraints on motion. An articulated object is modeled as a kinematic chain consisting of joints and links, and its 3D joint positions are estimated within a scale factor using the connection relationship of two links over two or three images. Then, twists and exponential maps are employed to represent the motion of each link, including the general motion of the base link and the rotation of other links around their joints. Finally, constraints from image point correspondences, which are similar to that of the essential matrix in rigid motion, are developed to estimate the motion. In the algorithm, the characteristic of articulated motion, i.e., motion correlation among links, is applied to decrease the complexity of the problem and improve the robustness. A point pattern matching algorithm for articulated objects is also discussed in this paper. Simulations and experiments on real images show the correctness and efficiency of the algorithms.
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