Title :
Recognition of planar objects in 3D space using a modified dynamic link architecture
Author :
Sim, H.C. ; Damper, R.I.
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Abstract :
Most object recognition systems are not invariant to perspective deformations. Hence, they are not suitable for general use in real world scenarios. This research aims at one of the fundamental subgoals leading to a realistic 3D object recognition system which is to detect flat objects in 3D space. In brief, the proposed system uses a new variant of neural processing known as dynamic link matching to achieve perspective invariant recognition even when the target is partially occluded in cluttered test images
Keywords :
image matching; neural net architecture; object recognition; self-organising feature maps; unsupervised learning; 3D object recognition system; 3D space; cluttered test images; dynamic link matching; flat objects; modified dynamic link architecture; neural processing; object recognition systems; partially occluded target; perspective deformations; planar objects recognition; unsupervised self-organization; Computer architecture; Computer science; Deformable models; Gabor filters; Image recognition; Indexing; Neurons; Object detection; Object recognition; System testing; Target recognition;
Conference_Titel :
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-8821-1
DOI :
10.1109/ICIP.1998.727329
