We propose a novel approach to pedestrian flow characterization. The definitions of density, flow and velocity existing in the literature are extended through a data-driven spatio-temporal discretization framework. The framework is based on three-dimensional Voronoi diagrams. The new definitions are (i) independent from an arbitrarily chosen discretization; (ii) appropriate for the multi-direct...

In the past decade, object detection has been researched to use a camera, a LIDAR and a RADAR. However, camera-based techniques have heavy image processing and are sensitive for light intensity. LIDAR can measure precise distance from objects, but it is difficult to classify objects. In addition, previous researches were unable to detect partially occluded pedestrian because the data to determi...

The Intermodal Simulator for the Analysis of Pedestrian Traffic (ISAPT) is being developed for the purpose of modeling pedestrian traffic within intermodal facilities, such that designers may evaluate the impact of building design on the Level of Service provided to pedestrians. The ISAPT system models each pedestrian’s behavior individually and the collective behavior of the crowd is allowed t...

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 ...

A paradigm to improve the quality of pedestrian movement by considering their interactions in the microscopic level is introduced. By this approach, design of pedestrian facilities is not merely space allocation but it can also utilize other form of flow controls in space, time and direction. Although microscopic pedestrian analysis exists, the microscopic pedestrian data collection has not bee...

Pedestrian detection is a vision task with many practical applications in video surveillance, road safety, autonomous driving and military. However, it is much more difficult compared to the detection of other visual objects, because of the tremendous variations in the inner region as well as the outer shape of the pedestrian pattern. In this paper, we propose a pedestrian detection approach th...

This article presents a novel method concerning pedestrian detection, thanks to graph kernels. Nowadays, the pedestrian detection is a hard task, due to the variability of its shape : size and posture. To address this problem, we choose to transform a pedestrian into a graph. The aim of this method consists of extracting a graph from each object (pedestrian or non-pedestrian), contained in a da...

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...