Spatiotemporal Directional Number Transitional Graph for Dynamic Texture Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Adín Ramírez Rivera, Oksam Chae

Abstract

Spatiotemporal image descriptors are gaining attention in the image research community for better representation of dynamic textures. In this paper, we introduce a dynamic-micro-texture descriptor, i.e., spatiotemporal directional number transitional graph (DNG), which describes both the spatial structure and motion of each local neighborhood by capturing the direction of natural flow in the temporal domain. We use the structure of the local neighborhood, given by its principal directions, and compute the transition of such directions between frames. Moreover, we present the statistics of the direction transitions in a transitional graph, which acts as a signature for a given spatiotemporal region in the dynamic texture. Furthermore, we create a sequence descriptor by dividing the spatiotemporal volume into several regions, computing a transitional graph for each of them, and represent the sequence as a set of graphs. Our results validate the robustness of the proposed descriptor in different scenarios for expression recognition and dynamic texture analysis.

References

Apr 14, 2007·IEEE Transactions on Pattern Analysis and Machine Intelligence·Guoying Zhao, Matti Pietikäinen
Nov 26, 2008·IEEE Transactions on Pattern Analysis and Machine Intelligence·Zhihong ZengThomas S Huang
Nov 17, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Guoying ZhaoMatti Pietikäinen
Dec 22, 2012·IEEE Transactions on Pattern Analysis and Machine Intelligence·Avinash RavichandranRené Vidal
Dec 28, 2012·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Adin Ramirez RiveraOksam Chae
Oct 8, 2014·IEEE Transactions on Cybernetics·Lin ZhongDimitris N Metaxas

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Citations

Mar 10, 2016·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Yimo GuoMatti Pietikainen

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