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.

Efficient hough forest object detection for low-power devices / Ciolini, Andrea; Seidenari, Lorenzo; Karaman, Svebor; Del Bimbo, Alberto. - ELETTRONICO. - (2015), pp. 1-6. (Intervento presentato al convegno 2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015 tenutosi a ita nel 2015) [10.1109/ICMEW.2015.7169857].

Efficient hough forest object detection for low-power devices

Seidenari, Lorenzo;Karaman, Svebor;Del Bimbo, Alberto
2015

Abstract

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.
2015
2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015
2015 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2015
ita
2015
Ciolini, Andrea; Seidenari, Lorenzo; Karaman, Svebor; Del Bimbo, Alberto
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1062055
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