Detecting changes in multilayered orthoimages with spatiotemporal texture blocks

A problem of detecting changes in a region viewed by multiple overlapping cameras is addressed. We are exploring a background change detection method of multilayered orthoimages using spatiotemporal texture blocks. Each camera view is projected to create a spatially aligned multilayered background orthoimages. The multilayered orthoimages are subdivided into non-overlapping blocks, and each block is represented by a 3D texture map. Texture maps are dimensionally reduced with principal component analysis. Motion detection is performed on each block and non-moving texture sections of the block are clustered into N-dimensional hyperspheres to discover changing patterns. The method evaluation is performed on publicly available surveillance video datasets.