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Representing Time-Varying 3D Point Clouds
Date: 2012/06/27
Time: 10:00 h
Place: P
Author(s): Dr. Sohaib Ahmad Khan, Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan

Am Mittwoch, den 27. Juni 2012, hält Dr. Sohaib Ahmad Khan um 10:00 Uhr im Raum P einen Vortrag mit dem Titel:

Representing Time-Varying 3D Point Clouds


A variety of dynamic objects, such as faces, bodies, and cloth, are represented in computer graphics as a collection of moving spatial landmarks. The principal modes of variation in the spatial geometry of objects are typically modeled using dimensionality reduction techniques, while concurrently, trajectory representations like splines and autoregressive models are widely used to exploit the temporal regularity of deformation. In this talk, I will present the bilinear spatiotemporal basis as a model that simultaneously exploits spatial and temporal regularity while maintaining the ability to generalize well to new sequences. The model can be interpreted as representing the data as a linear combination of spatiotemporal sequences consisting of shape modes oscillating over time at key frequencies. This factorization allows the use of analytical, predefined functions to represent temporal variation (e.g., BSplines or the Discrete Cosine Transform) resulting in more efficient model representation and estimation. We apply the bilinear model to natural spatiotemporal phenomena, including face, body, and cloth motion data, and compare it in terms of compaction, generalization ability, predictive precision, and efficiency to existing models. We demonstrate the application of this model to a number of graphics tasks including labeling, gap-filling, de-noising, and motion touch-up.

Bio: Sohaib Khan is Associate Professor and Department Chair of Computer Science at LUMS School of Science and Engineering, Lahore, Pakistan. His research interests broadly span the areas of image and video analysis, including estimating 3D from images, motion capture and multiple camera surveillance systems. Dr Khan earned his PhD degree in Computer Science in 2002 from University of Central Florida, specializing in computer vision. He was the associate editor of Machine Vision and Applications journal from 2008 - 2010. Dr Khan was awarded Hillman Award for Excellence in PhD Research in 2001 and Best Teacher Award by LUMS Computer Science Department in 2007.

Ref: Akhter et al. "Bilinear Spatiotemporal Basis Models", ACM Transactions on Graphics, April 2012