Spatiotemporal Gabor filters: a new method for dynamic texture recognition
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This paper presents a new method for dynamic texture recognition based on spatiotemporal Gabor filters. Dynamic textures have emerged as a new field of investigation that extends the concept of self-similarity of texture image to the spatiotemporal domain. To model a dynamic texture, we convolve the sequence of images to a bank of spatiotemporal Gabor filters. For each response, a feature vector is built by calculating the energy statistic. As far as the authors know, this paper is the first to report an effective method for dynamic texture recognition using spatiotemporal Gabor filters. We evaluate the proposed method on two challenging databases and the experimental results indicate that the proposed method is a robust approach for dynamic texture recognition.
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