Efficient 3D reflection symmetry detection: A view-based approach

• Propose a novel and efficient view-based symmetry detection algorithm.
• Demonstrate better accuracy and efficiency compared with two latest approaches.
• Dataset-level evaluation and two related applications validate good robustness and flexibility.

Symmetries exist in many 3D models while efficiently finding their symmetry planes is important and useful for many related applications. This paper presents a simple and efficient view-based reflection symmetry detection method based on the viewpoint entropy features of a set of sample views of a 3D model. Before symmetry detection, we align the 3D model based on the Continuous Principal Component Analysis (CPCA) method. To avoid the high computational load resulting from a directly combinatorial matching among the sample views, we develop a fast symmetry plane detection method by first generating a candidate symmetry plane based on a matching pair of sample views and then verifying whether the number of remaining matching pairs is within a minimum number. Experimental results and two related applications demonstrate better accuracy, efficiency, robustness and versatility of our algorithm than state-of-the-art approaches.

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