Challenge of multi-camera tracking

Wang, Yong; Lü, Ke; Zhai, Rui

doi:10.1109/cisp.2014.7003745

Cited by 6 publications

(1 citation statement)

References 42 publications

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“…c) MTT Under Multiple Cameras: Also called Multi-Target Multi-Camera (MTMC), this type of systems can be used to improve large tracking problems. Wang et al [227] presented a survey on the challenges of MTMC. One problem would be if the cameras angles overlap, in which case it is necessary to find a good way to fuse multiple information.…”

Section: C) Occlusionmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, interactive motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part I of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychology models, from the perspective of an AV designer. This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians. Technologies at these levels are found to be mature and available as foundations for use in high-level systems, such as behaviour modelling, prediction and interaction control.

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Section: C) Occlusionmentioning

confidence: 99%

Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking

Camara

Bellotto

Coşar

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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Literature Survey on Multi-Camera System and Its Application

2020

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A multi-camera system combines features from different cameras to exploit a scene of an event to increase the output image quality. The combination of two or more cameras requires prior settings in terms of calibration and architecture. Therefore, this paper surveys the available literature in terms of multi-camera systems' physical arrangements, calibrations, algorithms, and their advantages and disadvantages. We also survey the recent developments and advancements in four areas of multi-camera system applications, which are surveillance, sports, education, and mobile phones. In the surveillance system, the combination of multiple heterogeneous cameras and the discovery of Pan-Tilt-Zoom (PTZ) and smart cameras have brought tremendous achievements in the area of multi-camera control and coordination. Different approaches have been proposed to facilitate effective collaboration and monitoring among the camera network. Furthermore, the application of multi-cameras in sports has made the games more interesting in the aspect of analyses and transparency. The application of the multi-camera system in education has taken education beyond the four walls of the class. The method of teaching, student attendance enrollment, determination of students' attention, teacher and student assessment can now be determined with ease, and all forms of proxy and manipulation in education can be reduced by using a multi-camera system. Besides, the number of cameras featuring on smartphones is gaining noticeable recognition. However, most of these cameras serve different purposes, from zooming, telephoto, and wider Field of View (FOV). Therefore, future smartphones should be expecting more cameras or the development would be in a different direction.

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