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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Detecting mirror-symmetry of a volumetric shape from its single 2D image
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Tadamasa Sawada, Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
Zygmunt Pizlo, Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA
We present a new computational model for verifying whether a 3D shape is mirror-symmetric based on its single 2D image. First, a psychophysical experiment which tested human performance in detection of 3D symmetry is described. These psychophysical results led to the formulation of a new algorithm for symmetry detection. The algorithm first recovers the 3D shape using a priori constraints (symmetry, planarity of contours and 3D compactness) and then evaluates the degree of symmetry of the 3D shape. Reliable discrimination by the algorithm between symmetric and asymmetric 3D shapes involves two measures: similarity of the two halves of a 3D shape and compactness of the 3D shape. Performance of this algorithm is highly correlated with that of the subjects. We conclude that this algorithm is a plausible model of the mechanisms used by the human visual system.
Citation:
Tadamasa Sawada, Zygmunt Pizlo, "Detecting mirror-symmetry of a volumetric shape from its single 2D image," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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