Title :
Object Detection and Recognition via Deformable Illumination and Deformable Shape
Author :
Zhou, Qu ; Ma, L. ; Celenk, Mehmet ; Chelberg, David
Author_Institution :
Chrontel Inc., San Jose, CA, USA
Abstract :
Detecting and recognizing objects in unstructured environments is one of the most challenging tasks in computer vision research. We propose an innovative algorithm, called deformable illumination, to address the problem of illumination variance in natural environments. Parallel to the role of deformable shape in object recognition, deformable illumination is designed as an object detection technique. A unified framework presented here integrates both deformable illumination and deformable shape as a simultaneous scheme for object detection and recognition in unstructured environments. Experimental results show the effectiveness of deformable illumination in addressing illumination variance.
Keywords :
computer vision; object detection; object recognition; computer vision research; deformable illumination algorithm; deformable shape; illumination variance problem; natural environments; object detection; object recognition; unstructured environments; Active shape model; Deformable models; Image edge detection; Image segmentation; Layout; Lighting; Object detection; Object recognition; Principal component analysis; Shape measurement; Object detection; Object recognition;
Conference_Titel :
Image Processing, 2006 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
1-4244-0480-0
DOI :
10.1109/ICIP.2006.313113