A real-time visual attention system using integral images
Systems which simulate human visual attention are suited to quickly find regions of interest in images and are an interesting preprocessing method for a variety of applications. However, the scale-invariant computation of features in several feature dimensions applied to video streams at frame rate is still too time consuming for many practical applications. As a consequence, current implementations of attention systems often make compromises between the accuracy and speed of computing a focus of attention in order to reduce the computation time. In this paper, we present a method for achieving fast, real-time capable system performance with high accuracy. The method involves smart feature computation techniques based on integral images. An experimental validation of the speed gain of the attention system VOCUS is provided, too. The real-time capability of the optimized VOCUS system has already been demonstrated in robotic applications.