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Natural scene classification is a fundamental challenge in computer vision. By far, the majority of studies have limited their scope to scenes from single image stills and thereby ignore potentially informative temporal cues. The current paper is concerned with determining the degree of performance gain in considering short videos for recognizing natural scenes. Towards this end, the impact of multiscale...
Spatial Gabor energy filters (GE) are one of the most successful approaches to represent facial expressions in computer vision applications, including face recognition and expression analysis. It is well known that these filters approximate the response of complex cells in primary visual cortex. However these neurons are modulated by the temporal, not just spatial, properties of the visual signal...
This paper addresses the challenge of recognizing dynamic textures based on their observed visual dynamics. Typically, the term dynamic texture is used with reference to image sequences of various natural processes that exhibit stochastic dynamics (e.g., smoke, water and windblown vegetation); although, it applies equally well to images of simpler dynamics when analyzed in terms of aggregate region...
Dynamic texture is a part of the natural scene. For example, the landscape of fire, smoke, clouds and wind are dynamic textures. Dynamic texture recognition issue is research hotspot in the field of computer vision and even robot research area. In this paper this it is discussed in detail. First of all, we discuss the significance and status of dynamic texture recognition study. Some methods based...
A new algorithm is proposed for background subtraction in highly dynamic scenes. Background subtraction is equated to the dual problem of saliency detection: background points are those considered not salient by suitable comparison of object and background appearance and dynamics. Drawing inspiration from biological vision, saliency is defined locally, using center-surround computations that measure...
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