This paper presents a traffic simulation approach for evaluating the pedestrian behaviour by developing a model which includes pedestrians in a vehicular micro-simulation model i.e. PARAMICS that provides a default mechanism for simulating pedestrian movements. This approach is demonstrated by using a case study of a signalized intersection having large pedestrian flow interacting with large ve...

In the present paper scalar macroscopic models for traffic and pedestrian flows are coupled and the resulting system is investigated numerically. For the traffic flow the classical Lighthill-Whitham model on a network of roads and for the pedestrian flow the Hughes model are used. These models are coupled via terms in the fundamental diagrams modeling an influence of the traffic and pedestrian ...

In this paper, we propose a novel method with the multi-view Bayesian network (MBN) model to detect pedestrians from multi-camera surveillance videos. In our method, the ground plane is discretized in a predefined set of locations and our aim is to estimate the occupancy probability of each location that can be then used to predict the occurrence of pedestrians. To reduce the possible phantoms,...

Person re-identification (person re-ID) is mostly viewed as an image retrieval problem. This task aims to search a query person in a large image pool. In practice, person re-ID usually adopts automatic detectors to obtain cropped pedestrian images. However, this process suffers from two types of detector errors: excessive background and part missing. Both errors deteriorate the quality of pedes...

this research paper lays stress on philosophies of human desire. all the human being has some psychical need in addition to physical needs. and to satisfy the psychical needs, there is a need for stimulants, more in case of exclusive pedestrian precincts. having exclusively pedestrian precincts/cores in city design draws its inspiration from the fact that public zones, accessible to majority of...

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...

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...

Multispectral pedestrian detection is essential for around-the-clock applications, e.g., surveillance and autonomous driving. We deeply analyze Faster R-CNN for multispectral pedestrian detection task and then model it into a convolutional network (ConvNet) fusion problem. Further, we discover that ConvNet-based pedestrian detectors trained by color or thermal images separately provide compleme...

We propose a method for tracking multiple pedestrians using a binary sensor network. In our proposed method, sensor nodes are composed of pairs of binary sensors and placed at specific points, referred to as gates, where pedestrians temporarily change their movement characteristics, such as doors, stairs, and elevators, to detect pedestrian arrival and departure events. Tracking pedestrians in ...