Center for Image and Vision Science


            The Center for Image and Vision Science was established in 2002, affiliated with the departments of
    Statistics, Computer Science, and Psychology at UCLA.   Our research interest  is to pursue a general unified
    computational theory underlying visual perception and learning, and to build highly intelligent computer systems
    which understand real world imagery and interact with people and the real environment.
            Our projects span four directions:

            1.  Pursuing a unified theory for visual  learning and modeling. 
                         This includes learning a hierarchy of visual descriptions (vocabulary), and integrating descriptive and 
                         generative models for visual patterns such as  textures, textons, shapes, motion, face, text, clothes,
                         hair, plants,  lighting etc over scales.

            2.  Pursuing a unified theory for visual inference.
                         This integrates techniques from statistics, computer science, and math to form general algorithms
                         to search for globally optimal solutions  in complex and high dimensional search spaces. The key
                         emphasis is the unification of (bottom-up) discriminative inference with (top-down) generative
                         inference (MCMC and variational).
 
            3.  Pursuing new theoretical schemes for model complexity and computational complexity.
                         This provides metrics to measure  complexity of a vision problem and  here we should emphasize
                         ensemble complexity --- complexity averaged over the ensemble of images in contrast to worst case
                         complexity. The latter is almost aways NP-hard and has little relevance to real vision problems.
         
            4.  Applications:  image and video parsing, 3D scene reconstruction from 2D images, graphics rendering,
                         visual arts,  medical images, assisting visually blind and impaired population.

            We acknowledge the support from NSF, NIH, ONR, ARO, NASA, Keck Foundation, Sloan Foundation, 
    Microsoft, Kodak, and Siemens.

 Address: 8145 Math Sciences Bldg.                                     Telephone: 310-206-7721