ArrayFire Blog Parallelization of FOAGDD Point of Interest Extraction

(This is a guest post by Gustavo Stahl from São Paulo State University in Brazil.) Summary Corners present in images are widely used in multiple areas of computer science, such as augmented reality, autonomous vehicles, service robots, 3D reconstructions, object tracking, and many more. To work appropriately, applications in these areas usually rely on fast corner detectors with good-quality extractions. The FOAGDD (First-order Anisotropic Gaussian Direction Derivative) is an algorithmic technique for extracting corners in an image originally proposed by Weichuan Zhang and Changming Sun in 2019. The method surpassed the majority of extractors in corner detection quality but lacked speed, making it improper for real-time applications. Hence, this paper proposes transferring the workload from the original implementation to the ...Read More