Edgel templates for fast planar object detection and pose estimation

Taehee Lee, Stefano Soatto

Abstract: We describe a method to select edgels and to calculate gradient orientation-based template descriptors for edgel features. An edgel is selected within a grid block based on gradient magnitude; its position and orientation are used to determine a canonical frame where the descriptor is computed based on quantized orientation. The resulting descriptor is efficiently matched using logical operations. We demonstrate the use of the resulting edgel detection and description method for planar object detection and pose estimation.