A locally adaptive window for signal matching
International Journal of Computer Vision
Graphics gems IV
3-D Scene Data Recovery Using Omnidirectional Multibaseline Stereo
International Journal of Computer Vision
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
International Journal of Computer Vision
A Simple Stereo Algorithm to Recover Precise Object Boundaries and Smooth Surfaces
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multibaseline stereo system with active illumination and real-time image acquisition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Mesh Optimization Using an Inconsistency Detection Template
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Towards automatic visual obstacle avoidance
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
Computational Experiments with a Feature Based Stereo Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust and efficient photo-consistency estimation for volumetric 3d reconstruction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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In this article, we propose an efficient method for estimating a depth map from long-baseline image sequences captured by a calibrated moving multi-camera system. Our concept for estimating a depth map is very simple; we integrate the counting of the total number of interest points (TNIP) in images with the original framework of multiple baseline stereo. Even by using a simple algorithm, the depth can be determined without computing similarity measures such as SSD (sum of squared differences) and NCC (normalized cross correlation) that have been used for conventional stereo matching. The proposed stereo algorithm is computationally efficient and robust for distortions and occlusions and has high affinity with omni-directional and multi-camera imaging. Although expected trade-off between accuracy and efficiency is confirmed for a naive TNIP-based method, a hybrid approach that uses both TNIP and SSD improve this with realizing high accurate and efficient depth estimation. We have experimentally verified the validity and feasibility of the TNIP-based stereo algorithm for both synthetic and real outdoor scenes.