Natesh Srinivasan

Computer Science Ph.D. Student

School of Interactive Computing

College of Computing

Georgia Institute of Technology

Date: Monday, June 6th, 2016

Time: 11:00am to 1:00pm (EST)

Location: Marcus Nano Rm1116

Committee:

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Dr. Frank Dellaert (Advisor), School of Interactive Computing, Georgia Institute of Technology Dr. Irfan Essa (Co-Advisor), School of Interactive Computing, Georgia Institute of Technology Dr. James Hays, School of Interactive Computing, Georgia Institute of Technology Dr. Yanxi Liu, Department of Computer Science, University of Pennsylvania

Abstract:

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Generation of accurate 3D models of urban environments is an important problem that needs to be addressed in the modern society and cameras offer as a cheap and easy way to achieve this. I address the problem of reconstructing urban scenes exhibiting architectural symmetries from an image or a set of images. I propose a fully automatic algorithm that can identify multiple 3D symmetries that is not restricted to translational symmetries alone but also considers rotational and bilateral symmetries in 3D. In particular I make the following three major contributions :

1. I show that a voting scheme in a polar transformation coordinates can robustly detect 3D symmetries in noisy, distorted point clouds obtained from image based reconstruction and also provide a reasonable initialization for joint optimization of 3D structure and translational and rotational symmetries.

2. In cases where it is not possible to decouple the detection of symmetry and 3D reconstruction, I show that relaxing the constraints on feature matching to generate a “clique” of matches can be a useful method for both the detection of 3D symmetries and as a solution for incorrect correspondence arising as a consequence of symmetry. A symmetry-aware RANSAC stage in SfM can extract the relevant cliques that pertain to symmetry.

3. Finally I propoe that by explicitly modelling the 3D basis element using an object-centric coordinate system, we can eliminate the manual intervention needed to generate fully automatic algorithm for detecting symmetries in 3D and also obtain a dense element-wise reconstruction.