Analyzing and Abstracting Scans of Man-made Environments

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• Dr Niloy MItra, Reader, Dept of Computer Science, UCL
• Friday 21 March 2014, 14:00-15:00
• Cambridge University Engineering Department, LR3A.

If you have a question about this talk, please contact Rachel Fogg.

Rapid advances in scanning technologies have resulted in fast and easy acquisition of man-made environments. While such data (e.g., SfM, LiDAR, depth scans) can come in massive volumes, they do not, in their raw form, provide useful understanding of the environments. Such data provide a unique opportunity to discover and understand variability in shapes, both in terms of their geometry and arrangements. Our group has been investigating computational strategies to perform such analysis on raw scans to better understand the form and function of the world around us. In this talk I will present our latest attempts in this direction, while focusing on the underlying methodology and discussing the current challenges.

For details, please visit: http://vecg.cs.ucl.ac.uk/Projects/SmartGeometry/ http://www0.cs.ucl.ac.uk/staff/n.mitra/

Bio: Dr. Mitra is a Reader (Associate Professor) in the Department of Computer Science, University College London (UCL). Niloy received his MS (2002) and PhD (Sept. 2006) in Electrical Engineering from Stanford University under the guidance of Prof. Leonidas Guibas and Prof. Marc Levoy, and was a postdoctoral scholar with Prof. Helmut Pottmann at Technical University Vienna. Niloy’s research primarily centers around algorithmic issues in shape analysis and geometry processing. He is also interested in applying the analysis findings (e.g., relations, constraints, etc.) towards next generation design tools including smart shape synthesis and fabrication-aware functional model design. Niloy received the 2013 ACM Siggraph Significant New Researcher Award for “his outstanding work in discovery and use of structure and function in 3D objects” (UCL press release). He received the ERC Starting Grant on SmartGeometry in 2013.

This talk is part of the CUED Computer Vision Research Seminars series.

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