Focal-plane dynamic texture segmentation by programmable binning and scale extraction

Abstract

Dynamic textures are spatially repetitive time-varying visual patterns that present, however, some temporal stationarity within their constituting elements. In addition, their spatial and temporal extents are a priori unknown. This kind of pattern is very common in nature; therefore, dynamic texture segmentation is an important task for surveillance and monitoring. Conventional methods employ optic flow computation, though it represents a heavy computational load. Here, we describe texture segmentation based on focal-plane space-scale generation. The programmable size of the subimages to be analysed and the scales to be extracted encode sufficient information from the texture signature to warn its presence. A prototype smart imager has been designed and fabricated in 0.35μm CMOS, featuring a very low-power scale-space representation of used-defined subimages.