Artificial Visual Cortex and Random Search for Object Categorization

A random-ray model for Visual Search and Object Recognition

Object Templates for Visual Place Categorization

The Visual Place Categorization (VPC) problem refers to the categorization of the semantic category of a place using only visual information collected from an autonomous robot. Previous works on this problem only made use of the global configurations observation, such as the Bag-of-Words model and spatial pyramid matching. In this paper, we present a novel system solving the problem utilizing b...

Visual Categorization with Random Projection

Humans learn categories of complex objects quickly and from a few examples. Random projection has been suggested as a means to learn and categorize efficiently. We investigate how random projection affects categorization by humans and by very simple neural networks on the same stimuli and categorization tasks, and how this relates to the robustness of categories. We find that (1) drastic reduct...

Visual categorization and the parietal cortex

The primate brain is adept at rapidly grouping items and events into functional classes, or categories, in order to recognize the significance of stimuli and guide behavior. Higher cognitive functions have traditionally been considered the domain of frontal areas. However, increasing evidence suggests that parietal cortex is also involved in categorical and associative processes. Previous work ...

Fast Visual Object Identification and Categorization

Recently recognition and categorization of objects from images using local features has become very popular. While similar approaches have been used for identification and categorization tasks they have not been treated in a common framework. In this paper we present a method that treats visual object identification, categorization in a common framework by exploiting ideas from image interclass...