MULTI-PRIMITIVE HIERARCHICAL (MPH) STEREO ANALYSIS

被引:38
作者
MARAPANE, SB
TRIVEDI, MM
机构
[1] Computer Vision and Robotics Research Laboratory, Department of Electrical and Computer Engineering, University of Tennessee, Knoxville
基金
美国国家科学基金会;
关键词
COMPUTATIONAL BINOCULAR STEREO; HIERARCHICAL STEREO ANALYSIS; MULTIPLE PRIMITIVE ANALYSIS; DEPTH EXTRACTION;
D O I
10.1109/34.276122
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper develops and demonstrates a new computational framework for an accurate, robust, and efficient stereo approach. In multi-primitive hierarchical (MPH) computational model, stereo analysis is performed in multiple stages, incorporating multiple primitives, utilizing a hierarchical control strategy. The MPH stereo system consists of three integrated subsystems: region-based analysis module; linear edge segment-based analysis module; and edgel-based stereo analysis module. Results of stereo analysis at higher levels of the hierarchy are used for guidance at the lower levels. The MPH stereo system does not overly rely on one type of primitive and therefore will reliably work on a wide range of scenes. The MPH stereo analysis results in the generation of several disparity maps of multiple abstraction. Disparity maps generated at each level can be fused to obtain an accurate and fine resolution disparity map. The MPH approach also provides the capability to selectively analyze image regions with varying detail. This provides the means for adaptively extracting range information of only sufficient resolution. Thus, a stereo system that utilizes primitives of different abstraction and a multilevel hierarchical computational strategy will be superior to a single-level, single-primitive system. Extensive experimentation is carried out on a wide array of scenes of varying complexity from two application domains to systematically evaluate the validity and performance of the MPH framework. The MPH stereo system is able to analyze images in most cases with 85% - 100% matching accuracy in under a minute of processing time and yield depth values typically within +/-2% of the actual depth.
引用
收藏
页码:227 / 240
页数:14
相关论文
共 46 条
[1]  
ARNOLD RD, 1983, THESIS STANFORD U PA
[2]   EFFICIENT REGISTRATION OF STEREO IMAGES BY MATCHING GRAPH DESCRIPTIONS OF EDGE SEGMENTS [J].
AYACHE, N ;
FAVERJON, B .
INTERNATIONAL JOURNAL OF COMPUTER VISION, 1987, 1 (02) :107-131
[3]  
BAKER HH, 1981, 7TH P INT JOINT C AR, P631
[4]   DISPARITY ANALYSIS OF IMAGES [J].
BARNARD, ST ;
THOMPSON, WB .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1980, 2 (04) :333-340
[5]  
BARNARD ST, 1982, ACM COMPUT SURV, V14, P553
[6]   DYNAMIC EDGE WARPING - AN EXPERIMENTAL SYSTEM FOR RECOVERING DISPARITY MAPS IN WEAKLY CONSTRAINED SYSTEMS [J].
BOYER, KL ;
WUESCHER, DM ;
SARKAR, S .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1991, 21 (01) :143-158
[7]   STRUCTURAL STEREOPSIS FOR 3-D VISION [J].
BOYER, KL ;
KAK, AC .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1988, 10 (02) :144-166
[8]   A DISPARITY GRADIENT LIMIT FOR BINOCULAR FUSION [J].
BURT, P ;
JULESZ, B .
SCIENCE, 1980, 208 (4444) :615-617
[9]  
Chung R. C., 1991, Proceedings 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (91CH2983-5), P50, DOI 10.1109/CVPR.1991.139660
[10]  
COCHRAN SD, 1989, MAY P IM UND WORKSH, V1, P856