Bei Xiao Assistant Professor Department of Computer Science
- Additional Positions at AU
- Faculty Member, Center of Behavioral Neuroscience, BCCN graduate program
- Degrees
- Post-Doc, Brain and Cognitive Sciences, MIT.
PhD, Neuroscience, University of Pennsylvania.
BS, Chemistry, Tsinghua University, China.
- Languages Spoken
- Chinese, English, German
- Bio
- Dr. Bei Xiao's research focuses on how the human visual system estimate physical properties of objects in our surroundings. Another focus of her research is to apply results from human vision to develop robust computer vision algorithms. Specifically, she studies perception and recognition of material properties, 3D shape, tactile properties, of objects in dynamic scenes. She uses a combination of human psychophysics, crowd-sourcing, haptic force-feedback, computer graphics, machine learning, image processing and VR techniques. She did her undergraduate work in chemistry at Tsinghua University, China. She received her PhD in Neuroscience from University of Pennsylvania and did her post-doctoral research at The Smith-Kettlewell Eye research Institute in San Francisco and Brain and Cognitive Sciences, CSAL at MIT, Cambridge.
- See Also
- Personal homepage
- For the Media
- To request an interview for a news story, call AU Communications at 202-885-5950 or submit a request.
Teaching
Spring 2019
Scholarly, Creative & Professional Activities
Selected Publications
For full publication list, click here.
Wijntjes, M. and Xiao, B. Volvic, R. Visual communication of haptic material properties. (In Press). Journal of Vision.
Wenyan Bi. Newport, J, and Xiao, B. (2018). Interaction between static visual cues and force feedback on perception of mass of visual objects. 2018 ACM Symposium of Applied Peception (SAP).
Wenyan B., Pin, J. Nienborg, H, and Xiao, B . (2018). Estimating mechanical properties of cloth from videos using dense motion trajectories: human psychophysics and machine learning. Journal of Vision, 18(5), 12-12.
Wenyan B. and Xiao, B. (2016). Perceptual constancy of mechanical properties of cloth under variation of external force. SAP ‘16, Proceedings of the ACM Symposium on Applied perception, 19-23.
Xiao,B. Wenyan, B, Xiaodan, J, Hanhan, W, and Edward., A. (2016) Can you see what you feel? Color and folding conditions affect visual-tactile material discrimination of fabrics. Journal of Vision, 2(1).
Xiao, B., Gkioulekas, I., Adelson, E., Zickler, T., and Bala, K. (2014). Looking against the light:How perception of translucency depends on lighting direction. Journal of Vision 14(3).
Akkaynak D., Treibitz T., Xiao, B . Gukan, U.A., Allen, J.J. Dermirci, U. and Hanlon, R.T. (2014) Use of commercial off-the-shelf (COTS) digital cameras for scientific data acquisition and scenespecific color calibration. Journal of Optical Society of America, A (31), 2
Bouman, K.L., Xiao, B . Bataglia, P., and Freeman, W.T. (2013). Estimating the Material Properties of Fabrics from Videos. International Conference in Computer Vision (ICCV).
Gkioulekas. I., Xiao, B., Zhao. S., Adelson, E., Zickler,T., and Bala, K. (2012). Perceptual dimensions of phase functions for translucent appearance. ACM Transaction on Graphics (TOG).
Xiao, B. Hurst, B., Maclntyre, L. and Brainard, D.H. (2012) The Color Constancy of Three-Dimensional Objects. Journal of Vision. 12(4:6).
Xiao, B. and Wade, A.R. (2010) Measurements of long-range suppression in human opponent Scone and achromatic luminance channels. Journal of Vision 10(13):10.
Xiao, B. and Brainard, D.H. (2008) Surface gloss and color perception of 3D objects. Visual Neuroscience, 2008: 25:371-385
Xiao, B. and Brainard, D.H. Color Perception of 3D objects: constancy with respect to variation of surface gloss (2006). Proceedings of ACM Symposium on Applied Perception in Graphics and Visualization (APGV06), 2006: 63-68.
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, 2006: 6, 1277-1281.
Research Interests
Human Vision, Multisensory Percpetion, VR, Computer Vision, Machine Learning, Crowd-sourcing.