Scatter matrix based iterative structure and pose estimation from a single image

• Autorzy: Rodrigues M. A. , Liu Y. , Wei Q.
• Konferencja: Conference on Computer Graphics and Image Processing, GKPO' 2000 (6 ;15-19.05.2000 ; Polesie, Poland)
• Języki publikacji: EN

Abstrakty

EN

It has been demonstranted that the constraint least squeres (CLS) method yields accurate and robust motion parameter estimation from range images ([16,20]) assuming that the image data are corrupted by noise only without outliers. Also, it has been shown that scatter matrix based correspondenceless motion estimation from range images ([4]) is mathematically well defined. In this paper, we propose a new accurate and robust method for pose and strycture estimation from perspective images that draws on the good features of scatter matrix and constraint least squares methods. For reasons of parciticality and efficiency, the method first iteratively estimates the depth of some control points based on the constraints induced from the scatter matrix based correspondenceless motion estimation algorithm and then provides a closed from estimation of the depths of the other points based on rigid constraints. Finally, the method estimates pose parameters by the constraint least squares. For a comparative study of performance, we also omplemented a linear algorithm for pose estimation and a motion estimation algorithm based on epipolar geometry, [2, 24]. Experimental results based on both synthetic data and real images shown the relative superior performance of the proposed algoithm.

Słowa kluczowe

EN

Pose and structure estimation; constraint least squeres; scatter matrix; corespondencelees motion estimation; perspective image; range image

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2000
• Tom: Vol. 9, No. 1/2
• Strony: 525--538
• Opis fizyczny: Bibliogr. 24 poz.

Twórcy

autor

Rodrigues M. A.

autor

Liu Y.

autor

Wei Q.

• Intelligent Systems Research Group, School of Computing and Management Sciences, Sheffield Hallam University, Sheffield S1 1WB, UK