Abstract People counting has been investigated extensively as a tool to increase the individual’s safety and avoid crowd hazards at public places. It is challenging task especially in high-density environment such Hajj Umrah, where millions of people gathered constrained perform rituals. This due large variations scales across different scenes. To solve scale problem, simple effective solution ...

This article proposes a novel learning-based control policy with strong generalizability to new environments that enables mobile robot navigate autonomously through spaces filled both static obstacles and dense crowds of pedestrians. The uses unique combination input data generate the desired steering angle forward velocity: short history lidar data, kinematic about nearby pedestrians, subgoal ...

In this paper, a belief based correlated topic model (BCTM) is proposed for the semantic region analysis of pedestrian motion patterns in the crowded scenes. The inputs of the BCTM can be holistic trajectories or fragments of trajectories. By integrating the sources, sinks, and a forest of randomly spanning trees of trajectories as priors, the proposed BCTM improves the learning of semantic reg...

This paper presents a novel people detection and tracking method based on a multi-modal sensor fusion approach that utilizes 2D laser range and camera data. The data points in the laser scans are clustered using a novel graph-based method and an SVM based version of the cascaded AdaBoost classifier is trained with a set of geometrical features of these clusters. In the detection phase, the clas...

Humans navigate crowded spaces such as a university campus by following common sense rules based on social etiquette. In this paper, we argue that in order to enable the design of new target tracking or trajectory forecasting methods that can take full advantage of these rules, we need to have access to better data in the first place. To that end, we contribute a new large-scale dataset that co...

Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and mater...

We consider the problem of data association in a multiperson tracking context. In semi-crowded environments, people are still discernible as individually moving entities, that undergo many interactions with other people in their direct surrounding. Finding the correct association is therefore difficult, but higher-order social factors, such as group membership, are expected to ease the problem....