Abstract. We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose f...
In this paper, we propose an approach for fast pedestrian detection in images. Inspired by the histogram of oriented gradient (HOG) features, a set of multi-scale orientation (MSO...
This paper presents a new descriptor for human detection in still images. It is referred to as isotropic granularity-tunable gradients partition (IGGP), which is extended from gra...
By combining Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) as the feature set, we propose a novel human detection approach capable of handling partial occl...
On–board pedestrian detection is a key task in advanced driver assistance systems. It involves dealing with aspect–changing objects in cluttered environments, and working in a ...