Pedestrian safety is a primary traffic issue in the urban environment. According to national traffic safety data, more than 4,000 fatalities were caused by pedestrian-vehicle collisions annually among the 40,000-plus total fatalities in all categories of collisions. Pedestrian crashes account for about 80,000 collisions per year, according to the General Estimate System (GES) data from 1995 to ...

Bag detection in pedestrian images is a very practical visual surveillance problem. It is challenging because bag appearance may vary greatly. In this paper, we propose a novel two-stage approach for bag detection in pedestrian images. Firstly, we utilize two stripe vocabulary forests to check whether a pedestrian is with a bag. Secondly, we locate the bag location by ranking the generated bott...

Image acquisition mode of the CMOS sensor is active, charge photosensitive diode of the output by direct amplification transistor. Moving object scale change and deformation; moving target in the tracking process or rotary motion, change and camera distance and perspective, will cause the target image scale change and deformation. In this paper, with a pedestrian movement target specific, stati...

Driver assistance systems are being developed by automakers as mean to reduce traffic accidents. For examples, night vision systems that warn drivers of pedestrians during nighttime driving and pre-crash safety systems for collision mitigation have been commercialized in recent years, indicating that pedestrian detection will become an important function for driver assistance systems in the nea...

Pedestrian detection is among the most frequently-used preprocessing tasks in many surveillance application fields, from low-level people counting to high-level scene understanding. Even though many approaches perform well in the daytime with sufficient illumination, pedestrian detection at night is still a critical and challenging problem for video surveillance systems. To respond to this need...

In this paper, we present a pedestrian detection method based on the combination of Histograms of Oriented Gradient (HOG) feature and uniform local binary pattern (LBP) feature, which can detect pedestrian accurately. To the problem of low recognition rate for a single feature, we combine contour information and texture information, and propose the cascade of the two types of features, HOG feat...

Most of the pedestrian detection methods are based on hand-crafted features which produce low accuracy on complex scenes. With the development of deep learning method, pedestrian detection has achieved great success. In this paper, we take advantage of a convolutional neural network which is based on Fast R-CNN framework to extract robust pedestrian features for efficient and effective pedestri...

A program that detects people in images has a multitude of potential applications, including tracking for biomedical applications or surveillance, activity recognition for person-device interfaces (device control, video games), organizing personal picture collections, and much more. However, detecting people is difficult, as the appearance of a person can vary enormously because of changes in v...

Pedestrian detection is one of the key problems in emerging selfdriving car industry. And HOG algorithm has proven to provide good accuracy for pedestrian detection. There are plenty of research works have been done in accelerating HOG algorithm on FPGA because of its low-power and high-throughput characteristics. In this paper, we present a high-performance HOG architecture for pedestrian dete...

Pedestrians are the vulnerable participants in transportation system when crashes happen. It is important to detect pedestrian efficiently and accurately in many computer vision applications, such as intelligent transportation systems (ITSs) and safety driving assistant systems (SDASs). This paper proposes a two-stage pedestrian detection method based on machine vision. In the first stage, AdaB...