A testbed for distributed detection ofkeypoints and extraction of descriptors forthe Speeded-Up-Robust-Features (SURF)algorithm

Abstract: Detecting keypoints and computing descriptors needed in an imagerecognition algorithm are tasks that require substantial processing powerif they are to be executed in a short time span. If a network of sensornodes is used to capture the images to be processed, then the sensor nodescould be used to perform the actual processing. The system would dis-tribute the computing tasks to the available nodes in the network, so thatthe computing load can be divided among the nodes. By this, the com-puting time could possibly still be kept low, despite the large differencein available computing power between a rack-server and a sensor node.This report describes the implementation of a testbed for the evaluationof distributed processing of visual features. The testbed is implementedin C++ using creditcard sized computers and Zigbee USB units. Com-munication between nodes utilizes ASN.1 defined types. The detectionand extraction stage use an implementation of the SURF algorithm fromOpenCV. Results are sent for matching to a server using a TCP-socketin the sink node. The system is evaluated in terms of data transmissionprotocol efficiency, and time spent on transmitting data vs. computation.