Title :
A parallel network for the computation of structure from long-range motion
Author :
Laganière, R. ; Labrosse, F. ; Cohen, P.
Author_Institution :
Perception & Robotics Labs., Ecole Polytech. de Montreal, Que., Canada
Abstract :
The authors propose a parallel architecture for computing the 3-D structure of a moving scene from a long image sequence, using a principle known as the incremental rigidity scheme. At each instant an internal model of the 3-D structure is updated, based upon the observations accumulated until that time. The updating process favors rigid transformations but tolerates a limited deviation from rigidity. This deviation eventually leads the internal model to converge towards the actual 3-D structure of the scene. The main advantage of this architecture is its ability to accurately estimate the 3-D structure of the scene at a low computational cost. Testing has been successfully performed on synthetic data as well as real image sequences
Keywords :
computer vision; image recognition; motion estimation; parallel architectures; 3-D structure; incremental rigidity scheme; long-range motion; moving scene; parallel architecture; parallel network; real image sequences; structure computation; Computational efficiency; Computer architecture; Computer networks; Concurrent computing; Image converters; Image sequences; Layout; Parallel architectures; Performance evaluation; Testing;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227161