|
|
|
|
| LEADER |
03115nmm a2200385 u 4500 |
| 001 |
EB000720940 |
| 003 |
EBX01000000000000001350576 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
140122 ||| eng |
| 020 |
|
|
|a 9789401586689
|
| 100 |
1 |
|
|a Gang Xu
|
| 245 |
0 |
0 |
|a Epipolar Geometry in Stereo, Motion and Object Recognition
|h Elektronische Ressource
|b A Unified Approach
|c by Gang Xu, Zhengyou Zhang
|
| 250 |
|
|
|a 1st ed. 1996
|
| 260 |
|
|
|a Dordrecht
|b Springer Netherlands
|c 1996, 1996
|
| 300 |
|
|
|a XIX, 316 p
|b online resource
|
| 505 |
0 |
|
|a 1 Introduction -- 2 Camera Models and Epipolar Geometry -- 3 Recovery of Epipolar Geometry from Points -- 4 Recovery of Epipolar Geometry from Line Segments or Lines -- 5 Redefining Stereo, Motion and Object Recognition Via Epipolar Geometry -- 6 Image Matching and Uncalibrated Stereo -- 7 Multiple Rigid Motions: Correspondence and Segmentation -- 8 3D Object Recognition and Localization -- 9 Concluding Remarks -- References
|
| 653 |
|
|
|a Computer graphics
|
| 653 |
|
|
|a Image processing / Digital techniques
|
| 653 |
|
|
|a Computer vision
|
| 653 |
|
|
|a Computer Graphics
|
| 653 |
|
|
|a Electrical and Electronic Engineering
|
| 653 |
|
|
|a Electrical engineering
|
| 653 |
|
|
|a Computer Vision
|
| 653 |
|
|
|a Computer Imaging, Vision, Pattern Recognition and Graphics
|
| 653 |
|
|
|a Mechanical engineering
|
| 653 |
|
|
|a Mechanical Engineering
|
| 700 |
1 |
|
|a Zhengyou Zhang
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b SBA
|a Springer Book Archives -2004
|
| 490 |
0 |
|
|a Computational Imaging and Vision
|
| 028 |
5 |
0 |
|a 10.1007/978-94-015-8668-9
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-94-015-8668-9?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006
|
| 520 |
|
|
|a Appendix 164 3. A 3. A. 1 Approximate Estimation of Fundamental Matrix from General Matrix 164 3. A. 2 Estimation of Affine Transformation 165 4 RECOVERY OF EPIPOLAR GEOMETRY FROM LINE SEGMENTS OR LINES 167 Line Segments or Straight Lines 168 4. 1 4. 2 Solving Motion Using Line Segments Between Two Views 173 4. 2. 1 Overlap of Two Corresponding Line Segments 173 Estimating Motion by Maximizing Overlap 175 4. 2. 2 Implementation Details 4. 2. 3 176 Reconstructing 3D Line Segments 4. 2. 4 179 4. 2. 5 Experimental Results 180 4. 2. 6 Discussions 192 4. 3 Determining Epipolar Geometry of Three Views 194 4. 3. 1 Trifocal Constraints for Point Matches 194 4. 3. 2 Trifocal Constraints for Line Correspondences 199 4. 3. 3 Linear Estimation of K, L, and M Using Points and Lines 200 4. 3. 4 Determining Camera Projection Matrices 201 4. 3. 5 Image Transfer 203 4. 4 Summary 204 5 REDEFINING STEREO, MOTION AND OBJECT RECOGNITION VIA EPIPOLAR GEOMETRY 205 5. 1 Conventional Approaches to Stereo, Motion and Object Recognition 205 5. 1. 1 Stereo 205 5. 1. 2 Motion 206 5. 1. 3 Object Recognition 207 5. 2 Correspondence in Stereo, Motion and Object Recognition as 1D Search 209 5. 2. 1 Stereo Matching 209 xi Contents 5. 2. 2 Motion Correspondence and Segmentation 209 5. 2. 3 3D Object Recognition and Localization 210 Disparity and Spatial Disparity Space 210 5
|