An integrated framework for combining gist vision with object segregation categorisation and recognition

There are roughly two processing systems: (1) very fast gist vision of entire scenes, completely bottom-up and data driven, and (2) Focus-of-Attention (FoA) with sequential screening of specific image regions and objects. The latter system has to be sequential because unnormalised input objects must be matched against normalised templates of canonical object views stored in memory, which involves dynamic routing of features in the visual pathways.

Fast and accurate multi-scale keypoints based on end-stopped cells

Increasingly more applications in computer vision employ interest points. Algorithms like SIFT and SURF are all based on partial derivatives of images smoothed with Gaussian filter kemels. These algorithrns are fast and therefore very popular.