We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologic...
We describe the establishment of a compound object model for object recognition purposes which provides the frame for the extraction of object structure from images degraded by no...
We present a hierarchical system for object recognition that models neural mechanisms of visual processing identified in the mammalian ventral stream. The system is composed of ne...