Real-time visual attention on a massively parallel SIMD architecture

Visual attention is the ability to rapidly detect the visually salient parts of a given scene on which higher level vision tasks, such as object recognition, can focus. Found in biological vision, this mechanism represents a fundamental tool for computer vision. This paper reports the first real-time implementation of the complete visual attention mechanism on a compact and low-power architecture. Specifically, the saliency-based model of visual attention was implemented on a highly parallel single instruction, multiple data architecture called ProtoEye. Conceived for general purpose low-level image processing, ProtoEye consists of a 2D array of mixed analog–digital processing elements. To reach real-time, the operations required for visual attention computation were optimally distributed on the analog and digital parts. The currently available prototype runs at a frequency of 14 images=s and operates on 64 64 gray level images. Extensive testing and run-time analysis of the system stress the strengths of the architecture.