Talks & Seminars
Title: Detection and Characterization of Intrinsic Symmetry over 3D Shapes
Anirban Mukhopadhyay,
Date & Time: December 9, 2013 09:57
Venue: CSE Conf Room, First Floor
This talk will present a comprehensive framework for detection and characterization of partial intrinsic symmetry over 3D shapes. To identify prominent symmetric regions which overlap in space and vary in form, the proposed framework is decoupled into a correspondence space voting procedure followed by a transformation space mapping procedure. In the correspondence space voting procedure, significant symmetries are first detected by identifying surface point pairs on the input shape which are locally similar in their intrinsic geometry and maintain an intrinsic distance structure globally. Since different point pairs can share a common point, shape regions can potentially overlap. To this end, a global intrinsic distance-based voting technique is employed to ensure the inclusion of only point pairs that exhibit significant symmetry. In the transformation space mapping procedure, the Functional Map framework is employed to generate the final map of symmetries between point pairs. The transformation space mapping procedure ensures the retrieval of the underlying dense correspondence map throughout the 3D shape that follows a particular symmetry. Additionally, the formulation of a novel cost matrix enables the inner product to successfully indicate the complexity of the symmetry transformation. The proposed transformation space mapping procedure is shown to result in the formulation of a metric symmetry space where each point in the space represents a specific symmetric transformation and the distance between points represents the complexity between the corresponding transformations. Experimental results show that the proposed framework can successfully process complex 3D shapes possessing rich symmetries.
Speaker Profile:
Anirban Mukhopadhyay is a PhD Candidate of Computer Science Department and a part of Visual and Parallel Computing Laboratory at University of Georgia. His research mainly focuses on Geometric Analysis of Deformable Shapes and its application in Medical Image Analysis. He is a recipient of James L. Carmon Scholarship Award (2012) and MICCAI Society Travel Award (2012). He spent 2 summers as an intern in Siemens Corporate Research (Princeton, NJ) and Mitsubishi Electric Research Labs (Cambridge, MA). Mr. Mukhopadhyay serves as a reviewer in IEEE/ACM Transactions of Computational Biology and Bioinformatics.
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