At Spatial Cognition 2012, we will have three invited talks given by

• Bastian Leibe, RWTH Aachen, Mobile Multimedia Processing
• David Lubinski, Vanderbilt University, Vanderbilt Kennedy Center for Research on Human Development
• J. Kevin O'Regan, Université Paris Descartes, Laboratoire Psychologie de la Perception

Asbtract - Visual scene understanding in unconstrained scenarios of daily human living has been one of the main goals of Computer Vision since the field's beginnings. It is also a crucial requirement for many applications in the near future of mobile robotics and smart vehicles. While the general goal still poses considerable challenges, significant progress has been made in the development of mobile vision systems that can perform robust object detection and tracking in busy inner-city scenes. I will illustrate this progress on the example of a robotic vision system for real-time multi-person tracking which my group has (co-)developed within the EUROPA project.
Given this progress, it is appropriate to ask where do we stand? What are the scenarios we can already address with today's technology and where are the remaining challenges? Most importantly, what are the next steps we should focus on in order to make further progress? For this, I will show recent research results and point out some promising future directions.

Bio - Bastian Leibe is an associate professor at RWTH Aachen University, where he leads the Computer Vision group. He holds an M.Sc. degree from Georgia Institute of Technology (1999), a Diploma degree from the University of Stuttgart (2001) and a PhD from ETH Zurich (2004), all three in Computer Science. After completing his dissertation on visual object categorization at ETH Zurich, he worked as a postdoctoral research associate in the Multimodal Interactive Systems group at TU Darmstadt and in the Computer Vision Laboratory at ETH Zurich. During this time, he developed algorithms for multi-object detection and tracking from mobile platforms, as well as for 3D shape modeling and registration. Bastian Leibe has worked in EU projects CogVis, CoSy, DIRAC, Hermes and SCOVIS during his PhD and postdoc years and has been principal investigator for EU project EUROPA at RWTH. He has published over 70 articles in peer-reviewed journals and conferences. Over the years, he received several awards for his research work, including the Virtual Reality Best Paper Award in 2000, the ETH Medal and the DAGM Main Prize in 2004, the CVPR Best Paper Award in 2007, the DAGM Olympus Prize in 2008, the ICRA Best Vision Paper Award in 2009 and the ISPRS Journal of Photogrammetry and Remote Sensing Best Paper of the Year 2010 Award.

Asbtract - The importance of spatial ability in educational pursuits and the world of work are reviewed with particular attention devoted to STEM (science, technology, engineering & mathematics) domains. Then, recent findings from a 35-year longitudinal study will be reported: In the late 1970s, 563 intellectually talented 13-year-olds (identified by the SAT college-entrance examination as in the top 0.5% of ability), were assessed on spatial ability. Over 30 years later, their peer-reviewed publications and their patents were each classified into three groups. Spatial ability added incremental validity to the differential prediction of these accomplishments, beyond the SAT’s mathematical and verbal reasoning subtests. Findings support spatial ability’s unique role in the development of creativity, relative to traditional measures used in educational selection, counseling, and industrial-organizational psychology. In addition to modeling creativity and tracking intellectually talented youth over the lifespan, these findings reinforce prior evidence suggesting that assessing spatial ability is required for studying how intellectual development unfolds more generally. Spatial ability plays a key and unique role in structuring many important psychological phenomena, and warrants more widespread use across the applied and basic psychological sciences.

Bio - David Lubinski received both his B.A. (1981) and Ph.D. (1987) in psychology from the University of Minnesota. From 1987-1990 he was a fellow in the Postdoctoral Training Program in Quantitative Methods, Department of Psychology, University of Illinois (Champaign). He is currently Professor of Psychology at Vanderbilt University. With James H. Steiger, he co-directs the Quantitative Methods Area. With Camilla Benbow, he co-directs the Study of Mathematically Precocious Youth (SMPY), a planned 50-year longitudinal study of over 5,000 intellectually talented participants, begun in 1971.

His work has earned him the American Psychological Association's (APA) 1996 Distinguished Scientific Award for Early Career Contribution to Psychology (Applied Research/Psychometrics), APA's 1996 George A. Miller Award, the 1995 American Educational Research Association's Research Excellence Award (Counseling/Human Development), APA’s Templeton Award (2000) for Positive Psychology, APA’s Cattell sabbatical Award (2003-2004), and eight MENSA awards for research excellence. He is a member of the Society for Multivariate Experimental Psychology (SMEP) and has served as Associate Editor of the Journal of Personality and Social Psychology. He also serves on the board of the International Society for Intelligence Research (ISIR). In 2006, he received the Distinguished Scholar Award from the National Association for Gifted Children (NAGC).

Asbtract - Space seems to be given to us a priori, as a container which contains "stuff" like "objects" that can "move". Among the objects are our "bodies", which we can use to "act upon" the objects. These actions obey certain mathematical constraints dictated by the fact that space is three-dimensional and more or less Euclidean.
But for our brains such goings-on are only nerve firings, and nerve firings can occur without there being such a thing as space outside the body. So how can the nerve firings lead to space? Evolution may have built our brains to create space, but how can this have come about? What patterns of nerve firing enable this to be done?
The problem is complicated by the fact that sensory receptors do not signal spatial properties directly. For example in vision, distance is confounded with size; position is confounded with eye and body posture. In hearing, distance must be deduced from a combination of intensity and inter-aural time differences. Another problem is that in order to deduce spatial properties of the environment, the brain needs to know something about the body’s own spatial structure. And this is signalled by proprioceptive receptors whose outputs are also ambiguous. Finally, some a priori knowledge of body structure would seem to be necessary. So how can space arise from such a magma of neural firings?
When we think carefully about what space really is, we realize that we cannot hope to find space as a feature of the environment that is directly perceived. Space is a construction that allows us to describe our worlds more conveniently. It is a collection of invariants linking neural output to neural input.
Extracting such invariants must allow the brain to define concepts like "body", "environment", "action", "object", "position", "movement", "distance". Underlying such concepts are further facts like Separability: What I do here is generally not affected by what I do there; Relativity: Objects can be placed in the same spatial relation here as there; Impenetrability: Generally two objects cannot simultaneously occupy the same position; Group structure: some actions done on objects obey certain combinatorial rules independently of what the objects are. All of these notions are a few of many that are aspects of what we call space, but not all may be necessary for animals to function properly. Even humans’ notion of space may not rigorously encompass all these notions.
To understand better what are the basic concepts underlying the notion of space, a way to proceed is to build artificial agents of different degrees of complexity and see what notions of space they require in order to function. In my talk, I will present different agents illustrating different aspects of space, and will speculate how the underlying invariants could be learnt. I will show a naive agent that understands space as a set of "viewpoints from which things can be observed". I will show how this agent can determine the dimension of this space and acquire its metric properties.

J. Kevin O’Regan, Alban Laflaquière and Alexander Terekhov.