Proceedings Article10.1109/CVPR.2001.990925
Dynamic texture recognition
P. Saisan,Gianfranco Doretto,Ying Nian Wu,Stefano Soatto +3 more
- 01 Dec 2001
- Vol. 2, pp 58-63
395
TL;DR: This work poses the problem of recognizing and classifying dynamic textures in the space of dynamical systems where each dynamic texture is uniquely represented and examines three different distances in thespace of autoregressive models and assess their power.
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Abstract: Dynamic textures are sequences of images that exhibit some form of temporal stationarity, such as waves, steam, and foliage. We pose the problem of recognizing and classifying dynamic textures in the space of dynamical systems where each dynamic texture is uniquely represented. Since the space is non-linear, a distance between models must be defined We examine three different distances in the space of autoregressive models and assess their power.
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Citations
Autonomous Terrain Classification for Planetary Rover
Koki Fujita
- 23 Mar 2012
TL;DR: To improve autonomous mobility of planetary rover, many works have recently focused on non-geometric features of surrounding terrain such as color, texture, and wheel-soil interaction mechanics to utilize on-board sensors such as multi-spectral imagers, CCD cameras, laser range sensor, and accelerometer.
Statistical Analysis of Global Motion Chains
Jenny Yuen,Yasuyuki Matsushita +1 more
- 12 Oct 2008
TL;DR: This work model global motion as a multi-scale distribution of transformation matrices from frame to frame and quantifies the difference between pairs of videos using the KL-divergence of these distributions.
Indexation de Textures Dynamiques à l'aide de Décompositions Multi-échelles
Sloven Dubois,Renaud Péteri,Ménard Michel +2 more
- 24 Jan 2012
TL;DR: In this paper, six algorithmes de decomposition multi-echelle spatio-temporelle for the caracterisation de textures dynamiques are presented. And les algorithmes sont presentes et appliques avec succes sur trois bases consequentes de texture dynamiques disponibles en ligne.
1
•Journal Article
Chaotic Features for Dynamic Textures Recognition with Group Sparsity Representation
Xinbin Luo,Shan Fu,Yong Wang +2 more
TL;DR: A new algorithm for DT recognition based on group sparsity structure in conjunction with chaotic feature vector is proposed, which can be efficiently optimized through alternating direction method of multiplier algorithm.
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