Efficient hough forest object detection for low-power devices

An important task in computer vision is object localization and recognition within images and video. Achieving real-time object localization and recognition on low-power devices is especially relevant in the context of wearable technologies. Indeed, wearable devices have a reduced size and cost and limited computational power leading to a challenging scenario for classical computer vision algorithms. This paper improves the Hough Forest approach with several contributions: a faster computation of the features and a faster evaluation of the learned model with minimal loss in accuracy. Our method is characterized by a low computational requirement and allows real-time detection on a wearable device.