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In video surveillance to count the number of people walking through a corridor or door people counting is used. Counting persons passing through supervised area is important issue of this domain. System of people counting is important for security application (such as in the situation of an evacuation, it is vital to know how many people are present inside the surveillance area at any given time),...
This paper presents an unattended or removed Object detection method for video surveillance data captured by single static camera. Two backgrounds are modelled with different learning rates; one for transient and another for permanent. These both backgrounds are defined as a mixture of Gaussian model, it uses online Bayesian for updating. Two binary foregrounds are extracted by subtracting those backgrounds...
Over the past few years we have seen explosive growth in the amount of data and researchers are now facing greater challenges in dealing with heterogeneous data increasing in an unprecedented speed. There is a clear need for intelligent surveillance systems since the size of video data has become too large to be reviewed by humans. In this paper, we propose an unified computational framework, which...
The major challenge of video surveillance systems is the automated detection and interpretation of events of interest. In case of an abnormal event taking place, an alert should be delivered. Generally, a video surveillance system's framework combines three main phases: moving objects extraction, moving objects classification and tracking, scenario recognition. The last stage depends on the aimed...
Video surveillance systems that contain a large number of cameras makes the continuous monitoring of the video feeds nearly an impossible task. A transit or transportation authority usually deploys a video surveillance system to monitor and identify events in the system such as crowd behavior and crime. In this paper we present a method for automatically detecting people jumping or falling off a train...
In this paper, a selective eigenbackgrounds method is proposed for background subtraction in crowded scenes. In order to train and update the eigenbackground model with frames containing few objects (i.e. clean frames), virtual frames are constructed based on a frame selection map. Then, the eigenbackground that best depicts background is selected for each pixel based on an eigenbackground selection...
In this paper we introduce the WR (Workflow Recognition) dataset. Recorded in the production line of a major automobile manufacturer, this dataset consists of sequences that depict workers executing industrial workflows. The heavy occlusions, outliers, the visually complicated background and the human-machinery interaction are among the factors that make this dataset a very challenging testbed for...
This paper presents a video-based approach to traffic analysis and monitoring in night light conditions. In this kind of scenarios the headlights of the vehicles are the main features of the image taken from an urban or inter-urban traffic camera. The body of the vehicles is very low contrasted and many of the algorithms used in day-time decrease their performance. In our algorithm, we detect car...
Human detection in video streams is an important task in many applications including video surveillance. Surprisingly, only few papers have been devoted to this topic.
A video surveillance system is becoming more and more important for investigation and deterrent of crimes, and cameras installed in public space are increasing. However, a number of cameras is required to observe a wide and complex area with cameras installed at fixed positions. In order to efficiently observe a wide and complex area at lower cost, mobile robots have attracted attention. In this paper,...
With the prevalence of video surveillance systems, the demand for video quality assessment in terms of blur is raised quickly. In this paper, a fast and effective method based on distribution of gradient magnitudes is proposed. The moving foreground regions are first extracted based on adaptive background mixture models. Detections of two types of blur, the global blur and the partial blur, are classified...
Workflow recognition through processing of humans and objects in a camera sensor network, presents a significant challenge recently. Human action recognition and sequence of actions manipulation, that construct a workflow situation/rule, has many practical applications in many different real human application environments. This article presents a multi agent based real time infrastructure, for recognizing...
This paper describes the crowd image analysis challenge that forms part of the PETS 2010 workshop. The aim of this challenge is to use new or existing systems for i) crowd count and density estimation, ii) tracking of individual(s) within a crowd, and iii) detection of separate flows and specific crowd events, in a real-world environment. The dataset scenarios were filmed from multiple cameras and...
A master-slave camera surveillance system is composed of one(or more) wide FOV(field of view) static camera and one(or more) dynamic PTZ(Pan-Tilt-Zoom) camera. In such a system, master camera monitors a wide field and provides positional information of interesting objects to slave camera so that it can dynamically track them. This paper describes a novel method for the calibration of master-slave...
In this paper, we propose a novel appearance-based method for person re-identification, that condenses a set of frames of the same individual into a highly informative signature, called Histogram Plus Epitome, HPE. It incorporates complementary global and local statistical descriptions of the human appearance, focusing on the overall chromatic content, via histograms representation, and on the presence...
This paper presents an approach to count the number of people that enters or leaves metro trains. This is a challenging scenario where usually people crowd around the train doors, and therefore it is not possible a direct approach that segments and counts individuals. The proposed technique is based on a statistical analysis of the flow obtained from the motion vectors at corner points. The method...
As the number of older Americans increases and many decide to stay in their homes, the need for assistive technologies grows. One such technology is an intelligent system of surveillance cameras. While these systems can provide many services, we attempted to limit ourselves to the evaluation of systems that use cameras to track the locations of objects that may be lost or misplaced within a home....
In this paper we present a robust method for background subtraction from a fixed camera in video surveillance system. The background subtraction is an important part of object tracking and many algorithms have been proposed for decades. Mixture of Gaussian for those in this paper is very famous and used widely. We present the robust method that can adapt the background model to various situations...
Vessel dynamics video monitoring system is one of the most significant components in port safety and traffic management. This paper intends to discuss the key points in the design of the system: firstly, the data concerning vessel dynamics position are acquired via AIS; then intelligent video tracking system automatically drives intelligent spherical cameras to monitor vessels in port. Also system...
The aim of the paper is to present an approach for the localization of moving objects in a multi-camera system that is based on the estimation of observed objects' possible groundplane locations and motion statistics aggregation. It is flexible, it can handle arbitrary number of cameras. It uses only location and motion statistics and do not depend on appearance information. Due to its statistical...
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