A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
CAMP '05 Proceedings of the Seventh International Workshop on Computer Architecture for Machine Perception
Stereo Vision in Structured Environments by Consistent Semi-Global Matching
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Region-Tree Based Stereo Using Dynamic Programming Optimization
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Segment-Based Stereo Matching Using Belief Propagation and a Self-Adapting Dissimilarity Measure
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
High-Quality Real-Time Stereo Using Adaptive Cost Aggregation and Dynamic Programming
3DPVT '06 Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission (3DPVT'06)
Stereo vision enabling precise border localization within a scanline optimization framework
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
High-accuracy stereo depth maps using structured light
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A fast line segment based dense stereo algorithm using tree dynamic programming
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Fast and Robust Generation of Feature Maps for Region-Based Visual Attention
IEEE Transactions on Image Processing
Validating vision and robotic algorithms for dynamic real world environments
SIMPAR'10 Proceedings of the Second international conference on Simulation, modeling, and programming for autonomous robots
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In this paper we present a real-time scan-line segment based stereo vision for the estimation of biologically motivated classifier cells in an active vision system. The system is challenged to overcome several problems in autonomous mobile robotic vision such as the detection of incoming moving objects and estimating its 3D motion parameters in a dynamic environment. The proposed algorithm employs a modified optimization module within the scan-line framework to achieve valuable reduction in computation time needed for generating real-time depth map. Moreover, the experimental results showed high robustness against noises and unbalanced light condition in input data.