No abstract

No abstract

Abstract. In this paper we present a complete chain of algorithms for detection and tracking of moving objects using a static camera. The system is based on robust difference of images for motion detection. However, the difference of images does not take place directly over the image frames, but over two robust frames which are continuously constructed by temporal median filtering on a set of last grabbed images, which allows working with slow illumination changes. The system also includes a Kalman filter for tracking objects, which is also employed in two ways: assisting to the process of object detection and providing the object state that models its behaviour. These algorithms have given us a more robust method of detection, making possible the handling of occlusions as can be seen in the experimentation made with outdoor traffic scenes.

No abstract

Optimization in Rbbot Vision Architectures is a very complex issue. For one thing we have to consider cost and performance functions. As optimization criteria we propose to work with either constant cost or constant performance. In order to obtain some interesting results we need to work with simplified, well-aproximated models of the cost and performance functions and with these models w e propose a method to assess the benefit of variations in the configuration of the processors in an SIMD array based on the trade-off between the number and the complexity of the processors. Finally, this method is applied to some aspects of the design such as the datapath width and the reconfiguration capabilities.