Pedestrian detection is one of the important topics in computer vision with key applications in various fields of human life such as intelligent vehicles, surveillance and advanced robotics. In recent years, research related to pedestrian detection commonplace. This paper aims to review the papers related to pedestrian detection in order to provide an overview of the recent research. Main contr...

In this thesis, a novel Pedestrian Protection System (PPS), composed of the Pedestrian Detection System (PDS) and the Pedestrian Tracking System (PTS), was proposed. The PPS is a supplementary application for the Advanced Driver Assistance System, which is used to avoid collisions between vehicles and pedestrians. The Pedestrian Detection System (PDS) is used to detect pedestrians from near to ...

Driven by the prominent thermal signature of humans and following the growing availability of unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on the detection and tracking of pedestrians using thermal infrared images recorded from UAVs. However, pedestrian detection and tracking from the thermal images obtained from UAVs pose many challenges due to the low-res...

A novel pedestrian detection method based on the Four Direction Features (FDF), called FloatCascade pedestrian detection, is proposed for the pedestrian detection problem, which can be applied to the pedestrian detection problem in a single image. The FDF can represent pedestrian well, and the computation cost is lower than the HOG’s. FloatCascade applies the plus-l-minus-r method to select the...

With the increase of requirement for improving the safety of night driving, automatic pedestrian detection has received more and more attraction. This paper mainly introduces a pedestrian detection method in infrared images. Base on the properties of infrared images, we present a two-step pedestrian detection method including pedestrian candidate selection and validation. The first step is loca...

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of de...

Pedestrian detection is a hot topic in computer vision and pattern recognition. Existing pedestrian detection methods face new challenges in the background of big data, e.g., heavy burdens on computing and memory. To solve these problems, in this paper, we propose a pedestrian detection framework based on incremental learning. Compared with existing pedestrian detection frameworks, it costs muc...

We present a new method for obstacle and pedestrian detection with lower computation complexity and higher detection performance on a small target. By calculating stereo disparity according to the road parameters, our system efficiently detects objects above the ground. Experiments on over 10,000 images captured in urban areas demonstrate our method’s effectiveness. We also propose a multi-scal...

Pedestrian detection is an important application in computer vision. Currently, most pedestrian detection methods focus on learning one or multiple fixed models. These algorithms rely heavily on training data and do not perform well in handling various pedestrian deformations. To address this problem, we analyze the cause of pedestrian deformation and propose a method to adaptively describe the...