Abstract

While navigating in an environment, a vision system has' to be able to recognize where it is' and what the main objects' in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is' to identify familiar locations' (e.g., office 610, conference room 941, Main Street), to categorize new environments' (office, corridor, street) and to use that information to provide contextualpriors for object recognition (e.g., table, chair, car, computeD. We present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and how such contextual information introduces strong priors' that simplify object recognition. We have trained the system to recognize over 60 locations (indoors' and outdoors') and to suggest the presence and locations' of more than 20 different object types. The algorithm has been integrated into a mobile system that provides real-time feedback to the user. 1This work was sponsored by the Air Force under Air Force Contract F19628-00-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the author and are not necessarily endorsed by the U.S. Government.

Citations