•   When: Monday, November 13, 2023 from 11:00 AM to 12:00 PM
•   Speakers: Alla Sheffer, University of British Columbia
•   Location: Nguyen Engineering Bldg, Conference Room 4201
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Abstract:

Humans can ubiquitously communicate and reason about both tangible and abstract shape properties. Artists can succinctly convey complex shapes to a broad audience using a range of mediums; and human observers can effortlessly analyze and agree on observed shape properties such as upright-orientation or style. While perception research provides some clues as to the mental processes humans employ when performing these tasks, concrete and quantifiable explanations of these actions are frequently lacking. Our recent research aims to quantify the geometric properties underlying human shape communication and analysis, and to develop algorithms that successfully replicate human abilities in these domains. In my talk I will survey our efforts in this space, focusing on ways to incorporate insights about human perception into  algorithm design.  My talk will include examples across a wide range of 2D and 3D geometry processing tasks, including shape orientation, VR interfaces for shape modeling, raw sketch consolidation;  clip-art vectorization; clip-art reshaping;  sketch-based 3D reconstruction; and style analysis and transfer for man-made shapes. The common thread in our proposed solutions to these problems is the use of insights derived from perception and design literature combined with derivation of quantitative properties via targeted human perception studies and  machine learning from scarce data.

Biography:

Alla Sheffer is a Professor of Computer Science at the University of British Columbia and a Scholar at Amazon Inc. She received her BSc (1991), MSc (1995), and PhD (2000) from Hebrew University, Jerusalem, Israel. She investigates algorithms for geometry processing, focusing on fabrication and computer graphics applications. She is particularly interested in leveraging connections between geometry and perception to enable users to create and manipulate geometric content, including garments and 3D printable artifacts. Prof. Sheffer regularly publishes at selective computer graphics venues and has co-authored 52 papers published in ACM Transactions on Graphics, including numerous papers in SIGGRAPH and SIGGRAPH Asia proceedings. She holds 6 recent patents on methods for garment grading, sketch analysis, and hexahedral mesh generation. Sheffer is a Fellow of IEEE, a Fellow of ACM, a Fellow of the Royal Society of Canada, a Fellow of Eurographics, and a Member of the SIGGRAPH Academy. She is the recipient of the 2018 Canadian Human Computer Communications Society Achievement Award; a UBC Killam Research Award; multiple faculty awards from Adobe, Google and IBM; an NSERC Discovery Accelerator award; and an Audi Production Award. She is the Technical Papers Committee Chair for SIGGRAPH’23 and co-chaired the program committees for Eurographics’18, 3DV’18, PG’19, SGP’06 and IEEE SMI’13. She has served on the editorial boards of ACM TOG, IEEE TVCG, Computer Graphics Forum, Graphical Models, Computers & Graphics, and CAGD.