By Aleš Leonardis, Horst Bischof (auth.), Gerald Sommer, Kostas Daniilidis, Josef Pauli (eds.)
This e-book constitutes the refereed court cases of the seventh foreign convention on laptop research of pictures and styles, CAIP '97, held in Kiel, Germany, in September 1997.
The quantity provides ninety two revised papers chosen in the course of a double-blind reviewing approach from a complete of a hundred and fifty top quality submissions. The papers are prepared in topical sections on development research, item reputation and monitoring, invariants, functions, form, texture research, movement calibration, low-level processing, constitution from movement, stereo and correspondence, segmentation and grouping, mathematical morphology, pose estimation, and face analysis.
Read Online or Download Computer Analysis of Images and Patterns: 7th International Conference, CAIP '97 Kiel, Germany, September 10–12, 1997 Proceedings PDF
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Additional info for Computer Analysis of Images and Patterns: 7th International Conference, CAIP '97 Kiel, Germany, September 10–12, 1997 Proceedings
Zierl. HierarchicM Recognition of Articulated Objects from Single Perspective Views. In Computer Vision and Pattern Recognition. IEEE Computer Society Press, 1997. To appear. A. Hauck and N. O. StSffier. A Hierarchical World Model with Sensor- and [HS96] Task-Specific Features. In International Conference on Intelligent Robots and Systems, pages 1614-1621, 1996. K. Ikeuchi and T. Kanade. Automatic Generation of Object Recognition [IK88] Programs. IEEE Trans. on Computers, 76(8):1016-1035, August 1988.
On a standard SPARC 10 workstation the whole navigation task (image preprocessing and pose estimation) takes less than 2 seconds. Some results for the object recognition are presented in Fig. 6: On the left side the refinement of the rough 3D pose in Fig. 3 (b-c) is shown. 5. The other images in Fig. 6 show the 3D object recognition of the objects TOOLCARRIAGE and DRAWERCABINET. All of these tasks are perlbrmed in approx. 3 to 10 seconds on a SPARC 10, depending on the number of image and model features.
HORUS provides a large number of different image operators which are controlled by MORAL according to the performed task. Object-specific knowledge is used to control the image segmentation process. , lines, faces, arcs, and features like color of the foreground or background (Fig. 3 (a)). , the AMS task control or the user interface. 4 Object R e c o g n i t i o n The aim of the object recognition module is to identify objects and to determine their rough 3D pose by searching for the appropriate 2D model view matching the image.