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Wide baseline matching is the state of the art for object recognition and image registration problems in computer vision. Robust feature descriptors can give vast improvements in the quality and speed of subsequent steps, but intensive computation is still required. With the release of general purpose parallel computing interfaces, opportunities for increases in performance arise. In this paper we present an implementation of Speeded-Up Robust Feature (SURF) extractor, based on the OpenCLdoi:10.1007/978-0-387-31439-6_191 fatcat:qarlzawgt5hb5of4ccmxqhikl4