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Perceptual grouping via untangling Gestalt principles

Qi, Y., Guo, J., Li, Y., Zhang, H., Xiang, T., Song, Yi-Zhe and Tan, Z.-H. (2014) Perceptual grouping via untangling Gestalt principles In: 2013 Visual Communications and Image Processing (VCIP 2013), 17-20 Nov 2013, Kuching, Malaysia.

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Gestalt principles, a set of conjoining rules derived from human visual studies, have been known to play an important role in computer vision. Many applications such as image segmentation, contour grouping and scene understanding often rely on such rules to work. However, the problem of Gestalt confliction, i.e., the relative importance of each rule compared with another, remains unsolved. In this paper, we investigate the problem of perceptual grouping by quantifying the confliction among three commonly used rules: similarity, continuity and proximity. More specifically, we propose to quantify the importance of Gestalt rules by solving a learning to rank problem, and formulate a multi-label graph-cuts algorithm to group image primitives while taking into account the learned Gestalt confliction. Our experiment results confirm the existence of Gestalt confliction in perceptual grouping and demonstrate an improved performance when such a confliction is accounted for via the proposed grouping algorithm. Finally, a novel cross domain image classification method is proposed by exploiting perceptual grouping as representation.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Qi, Y.
Guo, J.
Li, Y.
Zhang, H.
Xiang, T.
Tan, Z.-H.
Date : March 2014
DOI : 10.1109/VCIP.2013.6706384
Uncontrolled Keywords : Gestalt confliction; RankSVM
Related URLs :
Additional Information : Printed proceedings published by Curran Associates Inc.
Depositing User : Clive Harris
Date Deposited : 12 Aug 2019 14:29
Last Modified : 12 Aug 2019 14:29

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