Abstract
This paper presents a neural vision system for real-time obstacle detection in front of a moving vehicle using linear stereo vision. The key problem is the correspondence task which consists of matching features in two stereo images that are projections of the same physical entity in the three-dimensional world. The linear stereo correspondence problem is formulated as an optimization task. An energy function, which represents the constraints on the solution, is mapped onto a Hopfield neural network for minimization. The system has been evaluated with experimental results on real stereo images.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
