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Selected Readings in
Vision and Graphics
edited by Luc Van Gool, Gábor Székely, Markus Gross, Bernt Schiele
Visual Urban Scene Analysis
by Moving Platforms
2009. XII, 240 pages. EUR 64,00.
In recent years, interest in mobile robots and intelligent vehicles that are able to act autonomously in scenarios of daily human living has been increasing constantly. Due to their relatively low price and similarity to human vision, cameras are an especially intriguing sensor for such tasks.
This book presents a purely vision-based system for the tasks of self-localization, scene analysis, and object tracking in semi-crowded urban environments, with a mobile platform as observer. To this end, several basic components are developed and integrated robustly. Taking this system as a basic component, its use for creating dynamic occupancy maps for path planning, for performing articulated multi-body tracking, and for improved pedestrian motion models inspired by social simulations is explored. Furthermore, a method for segmentation-based analysis of a traffic scene is proposed, which can infer the road type ahead of the observer as well as the presence of various object classes.
Experiments on challenging urban data corroborate the claim that sensor-related a majority of robotic tasks in daytime navigation and object tracking can be performed using vision only instead of using often considerably more expensive sensor arrays.
About the author:
Andreas Ess obtained his M.Sc. degree from ETH Zurich in 2005. From 2005 to 2009, he was research assistant and Ph.D. student at the Computer Vision Laboratory at ETH Zurich, with Prof. Luc Van Gool. He received his Ph.D. in Computer Science (Dr. sc. ETH Zurich) from ETH Zurich for his work on vision-based analysis of urban scenarios from moving platforms.
Keywords / Schlagwörter: object detection, object tracking, scene analysis, urban environments, moving platforms, stereo camera, motion models
Reihe " Selected Readings in Vision and Graphics "
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Hartung-Gorre Verlag / D-78465 Konstanz / Germany