Pedestrian safety is a major concern due to the vulnerability of pedestrians versus other traffic, especially in urban environment. The fatalities and injuries suffered in pedestrian collisions often intensify the perceived severity of these accidents. The problem is particularly significant for transit bus operations because their operations encounter pedestrian traffic regularly in their rout...

Data sets are a fundamental tool for comparing detection algorithms, fostering advances in the state of the art. The INRIA person data set is very popular in the Pedestrian Detection community, both for training detectors and reporting results. Yet, the labelling of its test set has some limitations: some of the pedestrians are not labelled, there is no specific label for the ambiguous cases an...

Pedestrian detection is the key technology in Advanced Driver Assistant System (ADAS).Until recently, pedestrian detection, which is realized as the vehicle equipment, still doesn't have the mature product. So, this thesis proposes a novel pedestrian detection system on board with the E-HOG (Histogram of Gradient) IP (intellectual property), can be used as the real time vehicle equipment. Three...

We report on a stereo system for 3D detection and tracking of pedestrians in urban traffic scenes. The system is built around a probabilistic environment model which fuses evidence from dense 3D reconstruction and image-based pedestrian detection into a consistent interpretation of the observed scene, and a multi-hypothesis tracker to reconstruct the pedestrians’ trajectories in 3D coordinates ...

Pedestrian detection method is the highest priority for “active safety” which prevents traffic accidents before happens. In previous studies, edge orientation based feature descriptors are proposed. Recently, high standard detection algorithm, Co-occurrence Histograms of Oriented Gradients (CoHOG) is proposed. However, this method has miss detection in complicated situation and processing cost ...

This paper presents a new approach for tracking multiple people in monocular calibrated cameras combining patch matching and pedestrian detection. Initially, background removal and pedestrian detection are used in conjunction with the vertical standing hypothesis to initialize the targets with multiples patches. In the tracking step, each patch related to a given target is matched individually ...

This paper describes a system for pedestrian detection in infrared images implemented and tested on an experimental vehicle. A specific stabilization procedure is applied after image acquisition and before processing to cope with vehicle movements affecting the camera calibration. The localization of pedestrians is based on the search for warm symmetrical objects with specific size and aspect r...

The present paper addresses pedestrian detection using local boosted features that are learned from a small set of training images. Our contribution is to use two boosting steps. The first one learns discriminant local features corresponding to pedestrian parts and the second one selects and combines these boosted features into a robust class classifier. In contrast of other works, our features...

This paper presents a new method for extracting pedestrian contours from images using 2D and 3D information obtained from a stereo-vision acquisition system. Two pedestrian contour types are extracted. First is obtained from static pedestrian confidence images using fixed background scenes and second from general traffic scenes having variable background. A robust approach for building contour ...

An effective and efficient visual word selection method based on Bag-of-features (BoF), which can be applied to the pedestrian detection problem, is proposed in this paper. We first calculate the difference in the total appearance frequency of each visual word in pedestrian and non-pedestrian images. Visual words that exhibit greater absolute values are more efficient for pedestrian detection, ...