Academic Commons


Integrating Sensory Data for Object Recognition Tasks

Allen, Peter K.; Bajcsy, Ruzena

Object recognition is a difficult task for single sensor systems (e.g. machine vision) in unconstrained environments. A useful approach is to combine sensory data from more than one source to overcome these problems. However, using multiple sensors poses new problems with respect to coordination of the sensors, strategies for their use and integration of their data. In this paper, these problems are explored and solutions posed for the task of object recognition using passive stereo vision and active tactile sensing.


Also Published In

Computer vision for robots : 2-6 December, 1985, Cannes, France

More About This Work

Academic Units
Computer Science
Society of Photo-optical Instrumentation Engineers
Proceedings of SPIE--The International Society for Optical Engineering, 595
Published Here
November 8, 2012
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.