Recursive 3-D Road and Relative Ego-State Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
The computation of optical flow
ACM Computing Surveys (CSUR)
Geometry of Distorted Visual Space and Cremona Transformation
International Journal of Computer Vision
Model-Based Brightness Constraints: On Direct Estimation of Structure and Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Maximum Likelihood Inference of 3D Structure from Image Sequences
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Motion and structure from multiple cues; image motion, shading flow, and stereo disparity
Computer Vision and Image Understanding
Towards direct recovery of shape and motion parameters from image sequences
Computer Vision and Image Understanding
A review and evaluation of methods estimating ego-motion
Computer Vision and Image Understanding
Hi-index | 0.00 |
This paper presents a method for the estimation of scene structure and camera motion from a sequence of images. This approach is fundamentally new. No computation of optical flow or feature correspondences is required. The method processes image sequences of arbitrary length and exploits the redundancy for a significant reduction in error over time. No assumptions are made about camera motion or surface structure. Both quantities are fully recovered. Our method combines the ``direct'''' motion vision approach with the theory of recursive estimation. Each step is illustrated and evaluated with results from real images.