Abstract:
In this paper, we propose an integrated system for scale-variance pedestrian detection. It consists of two cascaded components: a multi-layer detection neural network (ML...View moreMetadata
Abstract:
In this paper, we propose an integrated system for scale-variance pedestrian detection. It consists of two cascaded components: a multi-layer detection neural network (MLDNN) for scale-variance pedestrian detection, and a fast decision forest (FDF) for boosting detection performance with only a slight decrease in speed. Experimental results on the Caltech Pedestrian dataset show that our approach achieves state-of-the-art performance with a competitive speed.
Date of Conference: 24-27 October 2017
Date Added to IEEE Xplore: 21 December 2017
ISBN Information: