DocumentCode
253610
Title
Timing-Based Local Descriptor for Dynamic Surfaces
Author
Tung, Tony ; Matsuyama, Takashi
Author_Institution
Grad. Sch. of Inf., Kyoto Univ., Kyoto, Japan
fYear
2014
fDate
23-28 June 2014
Firstpage
414
Lastpage
421
Abstract
In this paper, we present the first local descriptor designed for dynamic surfaces. A dynamic surface is a surface that can undergo non-rigid deformation (e.g., human body surface). Using state-of-the-art technology, details on dynamic surfaces such as cloth wrinkle or facial expression can be accurately reconstructed. Hence, various results (e.g., surface rigidity, or elasticity) could be derived by microscopic categorization of surface elements. We propose a timing-based descriptor to model local spatiotemporal variations of surface intrinsic properties. The low-level descriptor encodes gaps between local event dynamics of neighboring keypoints using timing structure of linear dynamical systems (LDS). We also introduce the bag-of-timings (BoT) paradigm for surface dynamics characterization. Experiments are performed on synthesized and real-world datasets. We show the proposed descriptor can be used for challenging dynamic surface classification and segmentation with respect to rigidity at surface keypoints.
Keywords
image classification; image reconstruction; BoT; LDS; bag-of-timings paradigm; cloth wrinkle; dynamic surface classification; dynamic surface segmentation; facial expression; linear dynamical systems; local event dynamics; local spatiotemporal variations; low-level descriptor; microscopic categorization; neighboring keypoints; nonrigid deformation; real-world datasets; surface dynamics characterization; surface elements; surface intrinsic properties; surface keypoints; synthesized datasets; timing structure; timing-based local descriptor; Face; Hidden Markov models; Histograms; Shape; Surface reconstruction; Three-dimensional displays; Timing; classification; dynamic surface; dynamical system; local descriptor; timing structure;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location
Columbus, OH
Type
conf
DOI
10.1109/CVPR.2014.60
Filename
6909454
Link To Document