Perception of blending in stereo motion panoramas
ACM Transactions on Applied Perception (TAP)
Towards space-time semantics in two frames
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Spatiotemporal salience via centre-surround comparison of visual spacetime orientations
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
Efficient video quality assessment based on spacetime texture representation
Proceedings of the 21st ACM international conference on Multimedia
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This paper is concerned with the representation and recognition of the observed dynamics (i.e., excluding purely spatial appearance cues) of spacetime texture based on a spatiotemporal orientation analysis. The term “spacetime texture” is taken to refer to patterns in visual spacetime, (x,y,t), that primarily are characterized by the aggregate dynamic properties of elements or local measurements accumulated over a region of spatiotemporal support, rather than in terms of the dynamics of individual constituents. Examples include image sequences of natural processes that exhibit stochastic dynamics (e.g., fire, water, and windblown vegetation) as well as images of simpler dynamics when analyzed in terms of aggregate region properties (e.g., uniform motion of elements in imagery, such as pedestrians and vehicular traffic). Spacetime texture representation and recognition is important as it provides an early means of capturing the structure of an ensuing image stream in a meaningful fashion. Toward such ends, a novel approach to spacetime texture representation and an associated recognition method are described based on distributions (histograms) of spacetime orientation structure. Empirical evaluation on both standard and original image data sets shows the promise of the approach, including significant improvement over alternative state-of-the-art approaches in recognizing the same pattern from different viewpoints.