DocumentCode :
2762622
Title :
A factorization method using 3D linear combination for shape and motion recovery
Author :
Hwang, Kuo-chang ; Yokoya, Naokazu ; Takemura, Haruo ; Yamazawa, Kazumasa
Author_Institution :
Japan Syst. Co. Ltd., Tokyo, Japan
Volume :
2
fYear :
1998
fDate :
16-20 Aug 1998
Firstpage :
959
Abstract :
This study proposes a new factorization method for shape and motion recovery. In the past, the fourth greatest singular value of the measurement matrix was ignored. But when noise is large enough so that the fourth greatest singular value can not be ignored, it would be difficult to get reliable results by using the traditional factorization method. In order to acquire reliable results, We start with adopting an orthogonalization method to find a matrix which is composed of three mutually orthogonal vectors. By using this matrix, another matrix can be obtained. Then, the two expected matrices which represent shape of object and motion of camera/object, can be obtained through normalization. This study also conducts several experiments to discuss the feasibility of the proposed method
Keywords :
computer vision; image reconstruction; image sequences; motion estimation; singular value decomposition; stereo image processing; 3D object recovery; factorization; image sequences; motion recovery; normalization; orthogonalization; shape recovery; singular value decomposition; Calibration; Cameras; Electrical capacitance tomography; Ice; Linear approximation; Matrix decomposition; Noise shaping; Shape; Singular value decomposition; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1998. Proceedings. Fourteenth International Conference on
Conference_Location :
Brisbane, Qld.
ISSN :
1051-4651
Print_ISBN :
0-8186-8512-3
Type :
conf
DOI :
10.1109/ICPR.1998.711847
Filename :
711847
Link To Document :
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