Task oriented control of smart camera systems in the context of mobile service robots

In this paper we present our work on enabling smart cameras to act as autonomous vision systems for mobile service robots. The smart cameras will adapt their functionality to the current task of the robot system. Instead of transferring raw image data, higher level image information or regions-of-interest are transmitted. This way, the amount of data is reduced and computationally intensive image interpretation will not affect other tasks of the robot system. We are developing a flexible software solution to integrate smart camera systems to the architecture of our robot system. Each image processing task is constructed by a composition of modular functions that can be distributed over different systems. Timing aspects of the flow of data can be analyzed with different tools to evaluate the performance. For this work we are using a commercially available smart camera, but due to the use of a modular architecture the porting to other camera models is easy. We show the advantages of our approach in a setup where image regions containing a face are detected and extracted for further processing steps. This task is accomplished using different setups, where more or fewer subtasks are assigned to the camera system. The performance of the overall system is evaluated with respect to processor load, network load and latency of image data.