Computer graphics
Closed form solutions to image flow equations for planar surfaces in motion
Computer Vision, Graphics, and Image Processing
Flight simulation
Estimation of rigid body motion using straight line correspondences
Computer Vision, Graphics, and Image Processing
Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape From Texture: Integrating Texture-Element Extraction and Surface Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust regression methods for computer vision: a review
International Journal of Computer Vision
Determining straight line correspondences from intensity images
Pattern Recognition
Integrated 3D analysis and analysis guided synthesis
Integrated 3D analysis and analysis guided synthesis
Extraction of 2D Motion Trajectories and Its Application to Hand Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-based obstacle detection from image sequences
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
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This paper is concerned with three-dimensional (3D) analysis, and analysis-guided syntheses, of images showing 3-D motion of an observer relative to a scene. There are two objectives of the paper. First, it presents an approach to recovering 3D motion and structure parameters from multiple cues present in a monocular image sequence, such as point features, optical flow, regions, lines, texture gradient, and vanishing line. Second, it introduces the notion that the cues that contribute the most to 3-D interpretation are also the ones that would yield the most realistic synthesis, thus suggesting an approach to analysis guided 3-D representation. For concreteness, the paper focuses on flight image sequences of a planar, textured surface. The integration of information in these diverse cues is carried out using optimization. For reliable estimation, a sequential batch method is used to compute motion and structure. Synthesis is done by using (i) image attributes extracted from the image sequence, and (ii) simple, artificial image attributes which are not present in the original images. For display, real and/or artificial attributes are shown as a monocular or a binocular sequence. Performance evaluation is done through experiments with one synthetic sequence, and two real image sequences digitized from a commercially available video tape and a laserdisc. The attribute based representation of these sequences compressed their sizes by 502 and 367. The visualization sequence appears very similar to the original sequence in informal, monocular as well as stereo viewing on a workstation monitor.