Intelligent cameras and embedded reconfigurable computing: a case-study on motion detection

Abstract

Image processing for intelligent cameras like those used in video surveillance applications implies computational demanding algorithms activated in function of non predictable events, such as the content of the image or user requests. For such applications, hardwired acceleration must be restricted to a minimum subset of kernels, due to the increasing NREs when application update become necessary. Embedded reconfigurable processors, coupling in the same computing engine a general-purpose embedded processor and field-programmable fabrics, provide an appealing trade-off point between pure software and dedicated hardware acceleration. As a case-study, this paper presents the implementation of a set of image processing operators utilized for motion detection on the DREAM adaptive DSP. With respect to pure software solutions, the proposed implementation achieves a performance improvement of 2-3 orders of magnitude, while retaining the same degree of programmability and the same economical perspectives from the end-user point of view of processor-based approaches.