More Innovation from VCLA

Some members of our VCLA (Vision, Cognition, Learning and Art) research group (from left to right: Yibiao Zhao, Yixin Zhu and Steven Holtzen) are building a cognitive robot, which will not only navigate and recognize objects, but also make sense of the world like a human and answer meaningful questions beyond “what is where”. Answers relating to:

- Functionality: “What is the object used for?”
- Physics: “How likely will the object fall if someone bumps the table?”
- Intentionality: “Why the man left the room without closing the door? Will he come back?”
- Causality: “What did the man do if he come back with a cup of coffee?”

A central goal of computer vision is to create computational systems whose visual recognition and scene understanding accuracy is comparable to, or better than, that of biological vision. Over almost 50 years, the recognition of explicit visual patterns, like face and handwritten digits, has matured to the point of being ubiquitous in modern industrial and consumer products. However, computers still cannot perform many important tasks that are trivial for human vision. Recognizing man-made objects that vary greatly in appearance and shape, but not in function, such as chairs, and anticipating physical dangers, are examples of such tasks. This gap between people and computers exists because computers cannot use rich common sense knowledge about the functional, physical and social mechanics of the world in the ways that people can.

The group aims to close this gap by exploring methods for representing and exploiting common sense world knowledge about function, physics, intentions and causality in ways that can make human-level performance possible in machines. By treating function and physics as principal determinants in how a visual scene is organized by man or by nature, and by describing the relationships between visual entities and ongoing events using a rich notion of causality, computer vision systems can go beyond labeling “what is where” in an image to building a sophisticated understanding of a scene’s three-dimensional organization over time, its physical dynamics, and what actions it affords. In effect, these abilities allow a robot to answer an almost limitless range of questions about an image using a finite and general-purpose model. This may ultimately be instrumental to designing computers that can pass the visual Turing test.

A workshop "Vision meets cognition: functionality, physics, intentionality and causality" is being co-organized by Yibiao Zhao in conjunction with CVPR 2014. This will bring together researchers from different sub-communities within computer vision, computer graphics, robotics and cognitive science, to illuminate and broaden interdisciplinary awareness and collaboration.

Two UCLA Statistics Faculty Win Prestigious "PAMI Helmholtz Test-of-Time Award"

Congratulations to Song-Chun Zhu and Alan Yuille who won the “PAMI Helmholtz Test-of-Time Award”. This was awarded by the IEEE PAMI Technique Committee at the International Conference on Computer Vision (ICCV) held in Sydney in December 2013. They received this honor for the paper entitled, “Region Competition: Unifying Snakes, Region Growing, and Bayes / MDL for Multiband Image Segmentation”, which they co-authored in 1996. The paper developed a new algorithm called “Region Competition” which first linked statistical models of images to partial differential equations (PDEs) for image segmentation. The paper that wins the “PAMI Helmholtz Test-of-Time Award” is one that is frequently cited by other papers in computer vision, judged to have made a powerful impact to the field and must have been published by ICCV more than a decade ago.

Statistics/Social Sciences Tenure Track Faculty Position

Open-ranked tenured and tenure track position, joint in the Department of Statistics and a department or departments in the Division of Social Sciences at the University of California, Los Angeles. We seek a faculty member contributing at the cutting edge to the development of statistical methodology relevant to the social sciences. We welcome candidates whose experience in teaching, research or community service has prepared them to contribute to our commitment to diversity and excellence. Duties include new course development, teaching, and methodological and collaborative research. Ph.D. required by date of anticipated appointment of July 1, 2014. Salary will be commensurate with education and experience. Please refer to Tracking Job #1015-1314-01 on all correspondence.

Reviews for the position begin October 1, 2013, and will continue until the position is filled. Interested applicants should apply at UCLA Academic Recruit at:

https://recruit.apo.ucla.edu/apply/JPF00072

Applicants should submit:

1) CV
2) Cover letter describing how their qualifications and interests would fit with the position description
3) Statement of Research
4) Statement of Teaching
5) Three letters of recommendation

For more information on the departments in the Division of Social Sciences see www.sscnet.ucla.edu.

All inquiries may be sent to Professor Mark Handcock at css@stat.ucla.edu.

UCLA is an Affirmative Action/Equal Opportunity Employer with a strong institutional commitment to excellence through diversity. Women and Minorities are especially encouraged to apply.

Announcing the R User Conference 2014 to be held from June 30 to July 3 2014 at UCLA

The annual useR! international R User conference is the main meeting of the R user and developer community. It is being held at UCLA from June 30 to July 3, 2014.  Please goto http://user2014.stat.ucla.edu for more details.