Nest-crowdcontrol Advanced Video-based Crowd Monitoring for Large Public Events
نویسندگان
چکیده
Current video surveillance systems still lack of intelligent video and data analysis modules for supporting situation awareness of decision makers. Especially in mass gatherings like large public events, the decision maker would benefit from different views of the area, especially from crowd density estimations. This article describes a multi-camera system called NEST and its application for crowd density analysis. First, the overall system design is presented. Based on this, the crowd density estimation method is explained. The graphical user interface consists of two components: a georeferenced dynamic heat-map visualization and an interactive video stream visualization. Both components allow a direct camera control. In addition, the system is equipped with an adaptive privacy masking for privacy protection.
منابع مشابه
Recognition of Visual Events using Spatio-Temporal Information of the Video Signal
Recognition of visual events as a video analysis task has become popular in machine learning community. While the traditional approaches for detection of video events have been used for a long time, the recently evolved deep learning based methods have revolutionized this area. They have enabled event recognition systems to achieve detection rates which were not reachable by traditional approac...
متن کاملCrowd Behavior Recognition for Video Surveillance
Crowd behavior recognition is becoming an important research topic in video surveillance for public places. In this paper, we first discuss the crowd feature selection and extraction and propose a multiple-frame feature point detection and tracking based on the KLT tracker. We state that behavior modelling of crowd is usually coarse compared to that for individuals. Instead of developing genera...
متن کاملAbnormal Crowd Motion Detection with Hidden Conditional Random Fields Model
Crowd motion analysis in public places is an important research subject in the monitoring field. This paper proposes an approach for detecting abnormal crowd motion using Hidden Conditional Random Fields Model (HCRF). This approach derives variations of motion patterns from direction distribution of the crowd motion obtained by the optical flow and these variations are encoded with HCRF to allo...
متن کاملNew insights into crowd density analysis in video surveillance systems. (Nouvelles méthodes pour l'étude de la densité des foules en vidéo surveillance)
Along with the widespread growth of surveillance cameras, computer vision algorithms have played a fundamental role in analyzing the large amount of videos. However, most of the current approaches in automatic video surveillance assume that the observed scene is not crowded, and is composed of easily perceptible components. These approaches are hard to be extended to more challenging videos of ...
متن کاملAn Abnormal Crowd Behavior Detection Algorithm Based on Fluid Mechanics
Abnormal crowd behavior detection is an advanced topic researched in fields of computer vision and digital image processing. The problems such as diversity of monitoring scene, different crowd density and mutual occlusion among crowds etc result in a low recognition rate for abnormal crowd behavior detection. In order to solve these problems, this paper combines a streakline model based on flui...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015