High-level vision: object recognition and visual cognition

Object recognition: shape-based recognition what is recognition? why object recognition is difficult. Approaches to object recognition: invariant properties and feature spaces parts and structural descriptions the alignment approach which is the correct approach?. The alignment of pictorial descriptions: using corresponding features the use of multiple models for 3-D objects aligning pictorial descriptions transforming the image or the models? before and after alignment. The alignment of smooth bounding contours: the curvate method accuracy of the curvature method empirical testing. Recognition by the combination of views: modelling objects by view combinations objects with sharp edges using two views only using a single view the use of depth values summary of the basic scheme objects with smooth boundaries recognition by image combinations extensions to the view-combination scheme psychophysical and physiological evidence interim conclusions: recognition by multiple views. Classifications: classification and identification the role of object classification class-based processing using class prototypes pictorial classification evidence from psychology and biology are classes in the world or in our head? the organization of recognition memory. Image and model correspondence: feature correspondence contour matching correspondence-less methods correspondence processes in human vision model construction compensating for illumination changes. Segmentation and saliency: is segmentation feasible? bottom-up and top-down segmentation extracting globally salient structures saliency, selection, and completion what can bottom-up segmentation achieve? Visual cognition and visual routines: perceiving inside and outside spatial analysis by visual routines conclusions and open problems the elemental operations the assembly and storage of routines routines and recognition. Sequence seeking and counter streams - a model for visual cortex: the sequence-seeking scheme biological embodiment summary. Appendices: alignment by feature the curvature method errors of the curvature method locally affine matching definitions.