Instruction-set extension for an ASIP-based SIFT feature extraction

Abstract

One of the key problems in the field of Computer Vision is recovering the geometry from multiple views of the same scene. A feature-based approach to solve the challenge of finding matching points in different views is the scale-invariant feature transform (SIFT). SIFT requires complex accelerated feature extraction combined with low energy requirements to meet the strict constraints of advanced driver assistance systems (ADAS) with regard to power consumption, processing speed and flexibility for future algorithms. This paper presents an application-specific instruction-set extension for a Tensilica Xtensa LX4 ASIP to accelerate a SIFT feature extraction and its evaluation. When compared to the same arithmetic functions processed on an ASIP without any extensions, basic elements of digital image processing and specialized SIFT processing tasks that are accelerated reach a significant speed-up factor for arithmetic functions of x1300. At the same time the accuracy of the SIFT features is preserved. The SIFT feature extraction on an extended processor was accelerated by a factor of x167 compared to the base processor. In addition, the proposed processor extensions maintain the full flexibility of an ASIP for a fast integration of future feature extractors for advanced driver assistance systems.