Three-dimensional motion computation and object segmentation in a long sequence of stereo frames
International Journal of Computer Vision
Occlusions and binocular stereo
International Journal of Computer Vision
The computation of optical flow
ACM Computing Surveys (CSUR)
What can two images tell us about a third one?
International Journal of Computer Vision
In Defense of the Eight-Point Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Fast Stereo Matching Using Rectangular Subregioning and 3D Maximum-Surface Techniques
International Journal of Computer Vision
3-D surface reconstruction from stereoscopic image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
A Theory of Shape by Space Carving
A Theory of Shape by Space Carving
Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score
International Journal of Computer Vision
View invariant head recognition by Hybrid PCA based reconstruction
Integrated Computer-Aided Engineering
Correlation-based particle filter for 3D object tracking
Integrated Computer-Aided Engineering
Mixed color/level lines and their stereo- matching with a modified Hausdorff distance
Integrated Computer-Aided Engineering
Human automatic detection and tracking for outdoor video
Integrated Computer-Aided Engineering
Reconstruction of occluded facial images using asymmetrical Principal Component Analysis
Integrated Computer-Aided Engineering
Detection and classification of road signs for automatic inventory systems using computer vision
Integrated Computer-Aided Engineering
| Hi-index | 0.00 |
In the present work the problem of reconstructing locations of events in an arbitrary scene, or "world" for example 3D scene in real applications from an over-complete set of measurements, typically of lower dimension each such as multiple 2D images obtained from different cameras is addressed. A non-parametric approach based on Principal Component Analysis PCA has been developed where a training set of points with known world-coordinates is used to reconstruct the forward and inverse transformation matrices from the scene to the measurement space. The technique does not use any a priori information about the data acquisition geometry or its parameters and can also identify degenerate cases where either the training or the measurement sets are insufficient to perform robust reconstruction. As a first illustration a simple test-set of objects and their 2D images has been presented in order to illustrate the validity of the method. The next realistic application involves a data set of explosions recorded from two high-speed cameras. The method successfully reconstructs the positions of the explosions and in addition their intensities were also quantified.