The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Symmetry is one of the most important cues for human and machine perception of the chaotic real world. For over three decades now, automatic symmetry detection from images/patterns has been a standing topic in com- puter vision. We observe a surge of new symmetry detection algorithms that go beyond simple bilateral symmetry detection. This paper presents a sys- tematic, quantitative evaluation of rotation, reflection and translation sym- metry detection algorithms published within the past 1.5 years. We provide a set of carefully chosen synthetic and real images that contain both single and multiple symmetries and a diverse range of computational challenges. We also provide their associated, hand-labeled ground truth. We propose a well-defined quantitative evaluation scheme for an effective validation and comparison of different symmetry detection algorithms. Our results indicate that even after several decades of effort, symmetry detection from real-world images remains a challenging, unsolved problem in computer vision.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Computational Symmetry

Number of pages: 17

Text Reference

Po-Chun Chen, James H. Hays, Seungkyu Lee, Minwoo Park, and Yanxi Liu, "A Quantitative Evaluation of Symmetry Detection Algorithms," tech. report CMU-RI-TR-07-36, Robotics Institute, Carnegie Mellon University, September, 2007

BibTeX Reference

@techreport{Hays_2007_5873,
   author = "Po-Chun Chen and James H. Hays and Seungkyu Lee and Minwoo Park and Yanxi Liu",
   title = "A Quantitative Evaluation of Symmetry Detection Algorithms",
   booktitle = "",
   institution = "Robotics Institute",
   month = "September",
   year = "2007",
   number= "CMU-RI-TR-07-36",
   address= "Pittsburgh, PA",
}

The Robotics Institute

Menu