报告题目1：Matting and Compositing of Transparent and Refractive Objects
报告题目2：Make it Home: Automatic Optimization of Furniture Arrangement
时间Time：7月5日星期四下午2点( July 5th, 2:00pm )
地点：浙江大学紫金港校区图书信息中心B楼CAD&CG国家重点实验室402室
报告人：Dr. Sai-Kit Yeung
主持人：任重副教授

Bio-data：Dr. Sai-Kit Yeung is currently an Assistant Professor at the Singapore University of Technology and Design (SUTD). Before joining SUTD, he had been a Postdoctoral Scholar in the Department of Mathematics, University of California, Los Angeles (UCLA). He was also a visiting student at the Image Processing Research Group at UCLA in 2008 spring and summer and at the Image Sciences Institute, University Medical Center Utrecht, the Netherlands in 2007 summer. He is an HKUST alumni, graduated with a BEng degree (First Class Honors) in Computer Engineering in 2003, received his MPhil degree in Bioengineering in 2005, and completed his PhD degree in Electronic and Computer Engineering in 2009, all from HKUST.

Title1: Matting and Compositing of Transparent and Refractive Objects
Abstract：We present a new approach for matting and compositing transparent and refractive objects in photographs. The key to our work is an image-based matting model, termed the attenuation-refraction matte (ARM), that encodes plausible refractive properties of a transparent object along with its observed specularities and transmissive properties. We show that an object's ARM can be extracted directly from a photograph using simple user markup. Once extracted, the ARM is used to paste the object onto a new background with a variety of effects, including compound compositing, Fresnel effect, scene depth, and even caustic shadows.
User-studies find our results favorable to those obtained with Photoshop as well as perceptually valid in most cases. Our approach allows photo-editing of transparent and refractive objects in a manner that produces realistic effects previously only possible via 3D models or environment matting. This work was presented in Siggraph 2011 at Vancouver.

Title2: Make it Home: Automatic Optimization of Furniture Arrangement
Abstract：We present a system that automatically synthesizes indoor scenes realistically populated by a variety of furniture objects. Given examples of sensibly furnished indoor scenes, our system extracts, in advance, hierarchical and spatial relationships for various furniture objects, encoding them into priors associated with ergonomic factors, such as visibility and accessibility, which are assembled into a cost function whose optimization yields realistic furniture arrangements. To deal with the prohibitively large search space, the cost function is optimized by simulated annealing using a Metropolis-Hastings state search step.
We demonstrate that our system can synthesize multiple realistic furniture arrangements and, through a perceptual study, investigate whether there is a significant difference in the perceived functionality of the automatically synthesized results relative to furniture arrangements produced by human designers. This work was presented in Siggraph 2011 at Vancouver.