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The focus of the project is outdoor mobile computer vision with all of its challenges. Mobile systems need to be compact and energy efficient and are frequently changing locations. Therefore they must be autonomous and perform processing locally. A number of challenges arise from these requirements for which the project aims to provide solutions: Being compact, there is not much space for a large number of sensors such as laser scanners, radar antennas and the like. The work in this project will focus on stereo vision but with two different types of cameras. Often a second camera is already available and stereo information increases detection accuracies. Each time the system moves it needs to adapt to the changing situation. This requires adaptive calibration and online learning. Mobile systems often work from batteries. In addition, there is not much space to include intricate cooling systems. Thus, the system must be designed to be very energy efficient. New approaches for dynamic power management will be explored in the project. To put the work into context, several applications from the area of traffic surveillance/toll enforcement will be implemented and tested in an application oriented setting.
Current traffic enforcement solutions are either very large and costly (section control, toll enforcement) or do not offer much in terms of image processing (radar speed control). The technological output of Mobi Trick makes it possible to design mobile solutions for traffic monitoring, vehicle identification and classification, intelligent incident detection and observation of driver behavior. Mobile devices are also more efficient in enforcement. Their transient nature makes them less predictable. Mobile systems can also react more flexibly to changing road situations such as construction sites.