Bei Xiao

     Assistant Professor
     Computer Science Department

     Psychology Department (Affiliated) 

     
      Contact: bxiao at american dot edu

    
     


                                                                 



About me

I am a faculty at the Department of Computer Science at American University. My research focuses on human and machine perception, especially perception of material properties of objects in complex and dynamic scenes.  My long-term goal is to understand the mechanisms underlying perception and action using natural tasks.  

Before starting at AU, I was a postdoctoral fellow in the perceptual science group under the supervision of Professor Ted Adelson in the Brain and Cognitive Sciences Department at MIT Between 2009 and 2011, I worked with Professor Alex Wade at the Smith-Kettlewell Eye Research Institute in San Francisco, where I investigated early visual processing of color and luminance signals using frequency-tagging and source-imaged EEG methodsI did my graduate work in human color vision with Professor David Brainard at the University of Pennsylvania.  I received my undergraduate degree in physical chemistry from Tsinghua University in Beijing, China. I conducted my bachelor thesis research on thermodynamics of lipid bilayers with Professor Zhiwu Yu

News

                      Bei was at the ECVP 2017 in Berlin and gave a talk in the symposium "Beyond translation: Image deformation and dynamics in material and shape perception".
  
The Optical Society Fall Vision Meeting will be held at American University, October 13-15, 2017. Bei is one of the local organizers. 


Open Positions

The lab currently has an opening for a PhD fellowship. The main topic of this PhD studentship is to understand material perception from images and videos using computer graphics, virtual reality, and computer vision tools.  The ideal candidate should have a strong technical background and have experience in at least one of the following methods: computational modeling, psychophysics, computer graphics, visual psychophysics, and applied math. Solid programming skills are highly desirable but not required. Candidates with backgrounds in cognitive science, computer science, applied math, physics, and any engineering fields are strongly encouraged to apply. Prospective graduate student  should contact me directly and are required to apply to the graduate program Behavior, Cognition, & Neuroscience Graduate Program at AU

In all inquiries, please send me your detailed CV, a brief description of research interests, your GPA, and specify your programming and analytical skills. 

Group Members

Wenyan, Bi.  BS, Psychology, Beijing Normal University. Ph.D student, American University. Cloth Simulation and Perception. 
Simin Li. High School Student Researcher, Mongomery Blair High School. Machine learning.

Former Group Members

William Kistler, MA, American University. Research Assistant & Scientific Programmer 
Alex Perepechko, Senior, CS & Audio Technology major, American University. 
Laura Urilbe, Senior, CS major, American University
Yuuki Kpa, Sophomore, CS & Neuroscience double major, American University. 
Luis Bermudez, BS, Carnegie Mellon University. Research Assistant & Scientific Programmer.
Abhinav Swaminathan, Freshman, CS major, American University. Computer graphics. 


Research 

My research lies at the intersections of human and machine perception, and computer graphics. My goal is to understand how humans and machines estimate physical properties of objects from multi-sensory cues and use these to predict the future behavior of objects in the environment.  To do so, I use a combination of visual psychophysics, image analysis, and computer graphics.

Currently, the lab works on three general directions:
1) Perception and rendering of translucent appearance.
2) Perceptual inference of material properties of deformable objects in dynamic scenes. 
3) Interaction and integration between tactile and visual perception of material properties. 

Fields: Multi-sensory perception, computer inference of material properties and dynamic scenes, perception-driven computer graphics, computer vision. 
Techniques: Human psychophysics,  computer vision, computer graphics (3D modeling, rendering, animations), computational modeling, eye-tracking. 


Projects



                                       
             
             

  Speed of material and object recognition                                           
https://sites.google.com/site/beixiao/home/Screhttps://www.youtube.com/watch?v=LyI9sPFSqYA&feature=youtu.be
   

Publications

B, WY and Xiao, B. (2016).  Bi, WYand Xiao, B. (2016). Perceptual inference of mechanical properties of fabrics in dynamic scenes. ACM Symposium of Applied Perception (SAP 2016). PDF. Project Github Page. 

   
Xiao, B., Bi, W.Y., Jia, X-D,  Wei, HH, and Adelson, E. (2016). Can you see what you feel? Color and folding properties affects visual-tactile material discrimination of fabrics.  Journal of Vision. PDF.  




https://github.com/DavidBrainard/RenderToolbox3/wiki/Installing-RenderToolbox3 




Heasly, B.S., Cottaris, N.P., Lichtman, D.P., 
Xiao, B., Brainard, D.H. (2014). RenderToolbox3:MATLAB tools that facilitate physically-based stimulus rendering for vision research. Journal of Vision, Vol. 14, 2. PDFGitHub.



 




Xiao, B., Walter, B.W., Gkioulekas, I., Zickler, T., Adelson, E, and Bala, K. (2014). Looking against the light: how perception of translucency depends on lighting direction. Journal of Vision. 14(3): 17. PDF





Akkayanak, D. Treibitz, T., Xiao,B.,Gurkan, U.A., Allen, J.J.,Demirci, U., and Hanlon, R. (2014). Use of commercial off the shelf (COTS) digital cameras for scientific data acquisition and scene-specific color calibration. Journal of Optical Society of America A (JOSA A), Vol. 31, Issue 2, pp. 312-321. PDF, Online, MATLAB code.  


https://sites.google.com/site/beixiao/home/cloth0009_wind1_cropped5.png?attredirects=0 


Bouman, KL., Xiao,B., Battaglia, P., and Freeman, WT. (2013). Estimating the Material Properties of Fabrics From Video. International conference on computer vision (ICCV), 2013. PDF Video Datasets.
G
kioulekas, I., Xiao,B., Zhao, S., Adelson, E.H., Zickler, T., and Bala, K.(2013). Understanding the Role of Phase Function in Translucent Appearance. ACM Transactions on graphics (TOG). Volume 32, Issue 5.  PDFSupplemental MaterialsMedia coverage. This work was presented at SIGGRAPH 2013. 







Xiao, B., Hurst, B., MacIntyer, L. and Brainard, D.H. (2012). The Color Constancy of Three-Dimensional Objects.  Journal of Vision,12(4):6. PDF Supplemental Materials.                                                                                                






Xiao, B.
and Wade, A.R. (2010). 
Measurements of Long-range suppression in human opponent S-cone and achromatic luminance channels.  Journal of Vision 10(13):10. PDF                                                                                                                                                            





Xiao, B. and Brainard, D.H.(2008). Surface gloss and color perception of 3D objects. Visual Neuroscience, 25:371-385. PDF Supplemental Materials.                                                                                                                                                                      
                                                                                                                                                         




Xiao, B.
and Brainard, D.H. (2006).  
Color Perception of 3D objects: constancy with respect to variation of surface glossProceedings of ACM Symposium on Applied Perception in Graphics and Visualization (APGV06),  63-68. PDF                                                                                                                                                               





Brainard, D.H., Longere, P., Delahunt, P.B., Freeman, W.T., Kraft, J.M., and Xiao, B. (2006). 
Bayesian model of human color constancy.  Journal of Vision, 6, 1277-1281. PDF




Book Chapter

       Xiao, B.  (2016). Color Constancy, IEEE Encyclopedia of Color Science and Technology. PDF


Ph.D. Thesis

Xiao, B. (2009). Color Perception of 3D objects in Complex Scenes. Neuroscience Graduate Program, University of Pennsylvania, Philadelphia. Abstract  PDF

Selected Conference Presentations

       Wijntjes, M, and Xiao, B (2016).  Visual communications of haptic material properties. VSS 2016, St. Pete's Beach, Florida. Poster. 

       Bermudez, L. and Xiao, B. (2016). Estimating material properties of cloth from dynamic silhouettes.  VSS 2016, St.Pete's Beach, Florida. Poster. 

       Xiao, B., and  Kistler, W. (2015). Perceptual dimensions of material properties of fabrics in dynamic scenes.  VSS 2015, St.Pete's Beach, Florida. Talk.  
     
Xiao, B., and Kistler, W.  (2014). Perceptual dimensions of material properties of moving fabrics.  European Conference of Visual Perception (ECVP), Belgrade,  Serbia. Poster.

Xiao, B., Walter, B., Gkioulekas, I., Adelson,E., Zickler, T. and Bala, K.  (2014). Looking against the light: how perception of translucency depends on lighting direction and phase function. Vision Science Society Annual Meeting,  St.Pete's beach, FL. Abstract, Talk Slides.

Xiao, B., Adelson, E.  (2013). Multi-sensory understanding of material properties.  Prism2, The Science of Light and Shade. Bordeaux, France. 

Xiao, B., Jia, X.D., and Adelson, E.  (2013). Can you see what you feel? Visual and Tactile perception of fabrics. Vision Science Annual Meeting, Naples, FL. Poster

Xiao, B., Gkioulekas, I., Dunn, A, Zhao, S. Adelson,E., Zickler, T. and Bala, K.  (2012). Effects of shape and color on the perception of translucency. Vision Science Society Annual Meeting, Naples, FL. Talk Slides.

Xiao, B., Sharan. R, Rosenholtz. R. and Adelson,E. (2011). Speed of material vs. object recognition depends upon viewing conditions. OSA Fall Vision Meeting, Seattle, WA. Abstract, Slides.

Xiao, B., Wade, A.R. (2010). Interactions between S-cone and luminance signals in surround suppression. Vision Science Society Annual Meeting, Naples, FL. Abstract.

Xiao, B., Wade, A.R. (2009). Surround suppression between S-cone and luminance channels measured with psychophysics and source-localized EEG. OSA Fall Vision Meeting, Seattle, WA. Abstract. 

Xiao, B., Brainard, D.H. (2009). Surface material properties and color constancy of 3D objects. Vision Science Society Annual Meeting, Naples, FL. Abstract.


Software

           I am developing tutorials of image processing, computer vision, and psychophysical code with Python. For details, please see my Github page.

I use Python+Javascript to create external website for experiments to be run on Amazon Mechanical Turk. 

I use Rendertoolbox (Version 4), a MATLAB toolbox that drives modeling software Blender and rendering software Mitsuba and PBRT,  to create stimuli for vision research. I contributed to the first generation of this toolbox. 

I have written a Chi-Square test tutorial of psychophysics data. 

Workshops

       
The Science of Light and Shade, October 8th- 11th, 2013, Bordeaux, France. 

Computational Vision Summer School, June 28th-July 5th, 2012, Freudenstadt, Germany. 

Computational Neuroscience: Vision, July, 2006, Cold Spring Harbor, NY.


Collaborators

Main current and past collaborators:

Maarten Wijntjes, TU Delft

Kavita Bala, Cornell

Todd Zickler, Harvard

Bruce Walter, Cornell

Lavanya Sharan, Netflix

Shuang Zhao, UC Irvine

Xiaodan Jia, Oracle

Alex Wade, University of York, UK

David Brainard, University of Pennsylvania

Teaching 


My teaching interests include both core courses in computer science such as programming, as well as computer vision, image processing, human vision, and computational neuroscience, which are closer to my research field. 

CSC 589, Introduction to Computer Vision.  Fall, 2017. Introduction course in computer vision. The course will survey both low-level image processing methods such as filters, edge detection and color imaging, and also mid-to high-level tasks such as segmentation, clustering, and objects and scene understanding. Course Github Page.

CSC 435, Web Programming, Spring, 2016. This course introduces fundamental technologist behind web applications, focus on Javascript and server-side programming. 

CSC 280, Introduction to computer science, Fall 2015. This courses focused on introduction to programing and problem solving using Python. 

CSC 589, Introduction to Computer Vision.  Spring 2015. Introduction course in computer vision. The course will survey both low-level image processing methods such as filters, edge detection and color imaging, and also mid-to high-level tasks such as segmentation, clustering, and objects and scene understanding. Python Democodes on GitHub.

CSC 280, Introduction to computer science, Fall 2014. This will be an undergraduate introductory course to computer programming using Python. Besides learning basic syntax and data structure, this course emphasis on problem solving and also provides an introduction to data science and classical algorithms.

CSC 435, Web ProgrammingSpring, 2014. This is an advanced undergraduate level class of how to program on the web. The topics include HTML, CSS3, JavaScript, JQuery, PHP, SQL. Both front-and back-end programming methods are introduced. 

Other Interests

Music plays an important role in my life. Trained mostly in classical music, I play the piano and the harpsichord. I am always interested in playing chamber music with other musicians, especially vocalists and string musicians. 

DC has amazing concert series.  I especially like chamber music in small venues. My favorite classical/world music series in town are: