Cluttered Scene Segmentation Using the Symmetry Constraint

Add to your list(s) Download to your calendar using vCal

• Aleksandrs Ecins, University of Maryland
• Friday 18 March 2016, 10:00-11:00
• Dennis Gabor Seminar Room (611), EEE Department.

If you have a question about this talk, please contact Yiannis Demiris.

Rapid advances in robotic technology are bringing robots out of the controlled environments of assembly lines into the unstructured and unpredictable “real-world” workspaces of human beings. One of the prerequisites for operating in such environments is the ability to segment previously unseen objects. In this talk I will present an approach for object segmentation in 3D pointclouds of cluttered scenes based on the observation that the three-dimensional shape of common objects is bilaterally symmetric. Our approach consists of two tightly coupled steps. In the first step, candidate 3D bilateral symmetries are detected by extracting and matching surface normal edge curves of the pointcloud. In the second step objects are segmented by finding scene points that are consistent with a given symmetry candidate and at the same time satisfy the grouping principles of proximity and convexity. I will show the results of the experimental evaluation of this approach on a novel dataset of cluttered tabletop scenes and discuss why symmetry enables it to outperform current state-of-the-art approaches.

This talk is part of the Yiannis Demiris's list series.

This talk is included in these lists:

• Andrea Picciau's list
• COMMSP & CP list
• COMMSP Seminar
• Dennis Gabor Seminar Room (611), EEE Department
• Featured talks
• SAP Talks

Note that ex-directory lists are not shown.