scholarly journals Dynamic Object Path Detection in a Network of Surveillance Cameras

2013 ◽  
Vol 1 (1) ◽  
pp. 11-19
Author(s):  
H.H. Weerasena ◽  
P. B. S. Bandara ◽  
J.R.B. Kulasekara ◽  
B. M. B. Dassanayake ◽  
U. A. A. Niroshika ◽  
...  
Keyword(s):  
Moving Objects ◽  
Behavioral Changes ◽  
Surveillance Systems ◽  
Camera Network ◽  
Important Goal ◽  
Public And Private ◽  
3D Space ◽  
Detection And Tracking ◽  
Stereo Cameras ◽  
Camera Surveillance

Today, automated camera surveillance systems play a major role in securing public and private premises to ensure security and to reduce crime by detecting behavioral changes of moving objects. The important goal of such a surveillance system is to reduce human intervention while at the same time, provide accurate detection of moving objects. Many researchers have attempted to automate different aspects of camera surveillance such as tracking humans, traffic controlling, ground surveillance, etc. However, a system that overcomes overall difficulties that arise in the task of object detection and object tracking has not been developed because of high variance in the problem domain. The proposed system tracks the path of a locked object through a network of cameras. In contrast to traditional methods where the operators have to switch the screens manually to find the target objects, the proposed technique, once locked to an object; automatically tracks it through a camera network and generates the path on a map. We propose to use stereo cameras to enhance the detection and tracking of objects in 3D space.

scholarly journals Market-Based Approach to Mobile Surveillance Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Ahmed M. Elmogy ◽  
Alaa M. Khamis ◽  
Fakhri O. Karray
Keyword(s):  
Task Allocation ◽  
Critical Issue ◽  
Surveillance Systems ◽  
Public And Private ◽  
Detection And Tracking ◽  
Area Of Interest ◽  
Spatially Distributed ◽  
Decentralized Data Fusion ◽  
System Nodes ◽  
Mobile Surveillance

The active surveillance of public and private sites is increasingly becoming a very important and critical issue. It is, therefore, imperative to develop mobile surveillance systems to protect these sites. Modern surveillance systems encompass spatially distributed mobile and static sensors in order to provide effective monitoring of persistent and transient objects and events in a given area of interest (AOI). The realization of the potential of mobile surveillance requires the solution of different challenging problems such as task allocation, mobile sensor deployment, multisensor management, cooperative object detection and tracking, decentralized data fusion, and interoperability and accessibility of system nodes. This paper proposes a market-based approach that can be used to handle different problems of mobile surveillance systems. Task allocation and cooperative target tracking are studied using the proposed approach as two challenging problems of mobile surveillance systems. These challenges are addressed individually and collectively.

Automatic Objects Detection and Tracking Using FPCP, Blob Analysis and Kalman Filter

2020 ◽  
Vol 38 (2A) ◽  
pp. 246-254
Author(s):  
Hadeel N. Abdullah ◽  
Nuha H. Abdulghafoor
Keyword(s):  
Kalman Filter ◽  
Moving Objects ◽  
Response Speed ◽  
Noise Removal ◽  
Video Data ◽  
Detection Accuracy ◽  
Surveillance Systems ◽  
Detection And Tracking ◽  
Blob Analysis ◽  
Effective Role

Object detection and tracking are key mission in computer visibility applications, including civil or military surveillance systems. However, there are major challenges that have an effective role in the accuracy of detection and tracking such as the ability of the system to track the target and the response speed of the system in different environments as well as the presence of noise in the captured video sequence. In this proposed work, a new algorithm to detect moving objects from video data is designed by the Fast Principle Component Purist (FPCP). Then, we used an ideal filter that performs well to reduce noise through the morphological filter. The Blob analysis is used to add smoothness to the spatial identification of objects and their areas, and finally, the detected object is tracked by Kalman Filter. The applied examples demonstrated the efficiency and capability of the proposed system for noise removal, detection accuracy and tracking.

scholarly journals Real-Time detection and tracking moving vehicles for video surveillance systems using FPGA

2018 ◽  
Vol 7 (2.31) ◽  
pp. 117
Author(s):  
Mohammed Abdulraheem Fadhel ◽  
Omran Al-Shamaa ◽  
Bahaa Husain Taher
Keyword(s):  
Computer Vision ◽  
Video Surveillance ◽  
Moving Objects ◽  
Smart Cities ◽  
Autonomous Systems ◽  
Surveillance Systems ◽  
Detection And Tracking ◽  
Moving Vehicles ◽  
Communication Devices ◽  
Significant Application

With the growth of the electronic and communication devices, computer vision has become an significant application of smart cities. A smart city is controlled by smart autonomous systems. Many algorithms have been developed to satisfy these smart cities. This paper concerned with addressing the moving objects (vehicles) by using morphological techniques. For computational cheapness. The simulation has been built by a MATLAB 2012a and its implementation was done using Xilinx-ISE 14.6 (2013) XC3S700A-FPGA board that provides an exceptional tool for mixing between two platforms, the ISE 14.6(2013) and the MATLAB (2012a) platforms. MATLAB provides components for FPGA that invoke Verilog code of Xilinx platform, to avoid the size weakness of XC3S700A-FPGA board. 

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

scholarly journals Twelve Years of the Italian Program to Enhance Relational and Communication Skills (PERCS)

2021 ◽  
Vol 18 (2) ◽  
pp. 439
Author(s):  
Lidia Borghi ◽  
Elaine C. Meyer ◽  
Elena Vegni ◽  
Roberta Oteri ◽  
Paolo Almagioni ◽  
...  
Keyword(s):  
Communication Skills ◽  
Repeated Measures ◽  
Behavioral Changes ◽  
Chi Square ◽  
Future Directions ◽  
Public And Private ◽  
Learner Centered ◽  
Difficult Conversations ◽  
Booster Sessions ◽  
Before And After

To describe the experience of the Italian Program to Enhance Relations and Communication Skills (PERCS-Italy) for difficult healthcare conversations. PERCS-Italy has been offered in two different hospitals in Milan since 2008. Each workshop lasts 5 h, enrolls 10–15 interdisciplinary participants, and is organized around simulations and debriefing of two difficult conversations. Before and after the workshops, participants rate their preparation, communication, relational skills, confidence, and anxiety on 5-point Likert scales. Usefulness, quality, and recommendation of the program are also assessed. Descriptive statistics, t-tests, repeated-measures ANOVA, and Chi-square were performed. A total of 72 workshops have been offered, involving 830 interdisciplinary participants. Participants reported improvements in all the dimensions (p < 0.001) without differences across the two hospitals. Nurses and other professionals reported a greater improvement in preparation, communication skills, and confidence, compared to physicians and psychosocial professionals. Usefulness, quality, and recommendation of PERCS programs were highly rated, without differences by discipline. PERCS-Italy proved to be adaptable to different hospital settings, public and private. After the workshops, clinicians reported improvements in self-reported competencies when facing difficult conversations. PERCS-Italy’s sustainability is based on the flexible format combined with a solid learner-centered approach. Future directions include implementation of booster sessions to maintain learning and the assessment of behavioral changes.

Multi Object Detection and Tracking from Video File

2014 ◽  
Vol 533 ◽  
pp. 218-225 ◽  
Author(s):  
Rapee Krerngkamjornkit ◽  
Milan Simic
Keyword(s):  
Computer Vision ◽  
Background Subtraction ◽  
Moving Objects ◽  
Gaussian Mixture Models ◽  
Gaussian Mixture ◽  
Video Tracking ◽  
Partial Occlusion ◽  
Video File ◽  
Detection And Tracking ◽  
Over Time

This paper describes computer vision algorithms for detection, identification, and tracking of moving objects in a video file. The problem of multiple object tracking can be divided into two parts; detecting moving objects in each frame and associating the detections corresponding to the same object over time. The detection of moving objects uses a background subtraction algorithm based on Gaussian mixture models. The motion of each track is estimated by a Kalman filter. The video tracking algorithm was successfully tested using the BIWI walking pedestrians datasets [. The experimental results show that system can operate in real time and successfully detect, track and identify multiple targets in the presence of partial occlusion.

The Research of Moving Target Detection and Tracking System Based on DM6437

2015 ◽  
Vol 734 ◽  
pp. 203-206
Author(s):  
En Zeng Dong ◽  
Sheng Xu Yan ◽  
Kui Xiang Wei
Keyword(s):  
Target Detection ◽  
Digital Signal Processor ◽  
Moving Objects ◽  
Tracking System ◽  
Digital Signal ◽  
Gaussian Mixture ◽  
Background Model ◽  
Moving Target ◽  
Moving Target Detection ◽  
Detection And Tracking

In order to enhance the rapidity and the accuracy of moving target detection and tracking, and improve the speed of the algorithm on the DSP (digital signal processor), an active visual tracking system was designed based on the gaussian mixture background model and Meanshift algorithm on DM6437. The system use the VLIB library developed by TI, and through the method of gaussian mixture background model to detect the moving objects and use the Meanshift tracking algorithm based on color features to track the target in RGB space. Finally, the system is tested on the hardware platform, and the system is verified to be quickness and accuracy.

scholarly journals RESOURCE SUPPLY AN ACCESSIBILITY OF PUBLIC TRANSPORTATION FACILITIES

YMER Digital ◽  
2021 ◽  
Vol 20 (12) ◽  
pp. 446-455
Author(s):  
Eshetu Mathewos Juta ◽  
Keyword(s):  
Public Transportation ◽  
Lessons Learned ◽  
Assessment System ◽  
Behavioral Changes ◽  
Public And Private ◽  
The Public ◽  
Urban Mass Transit ◽  
Transportation Accessibility ◽  
Private Actors ◽  
Transportation Facilities

The term “urban mass transit” generally refers to scheduled intra-city service on a fixed route in shared vehicles. Public transportation is an important contributing factor to urban sustainability. Effective transportation networks that incorporate public transit livable by easing commute and transportation needs and increasing accessibility. To assess public transportation accessibility in metropolitan networks, two indices are used: the supply level of urban public transportation facilities resource and the public transportation-private automobile traveling time ratio. As the research in the Wolaita sodo town region and the assessment system, an evaluation technique for urban public transportation facility resource supply is developed based on accessibility. Accessibility is a representative indicator for evaluating the supply of bus system. Traditional studies have evaluated the accessibility from different aspects. Considering the interaction among land use, bus timetable arrangement and individual factors, a more holistic accessibility measurement is proposed to combine static and dynamic characteristics from multisource traffic data. The objective is to highlight the main lessons learned and identify knowledge gaps to guide the design and evaluation of future transport investments. Moreover, studies looking at ways to improve the operational efficiency of systems and those seeking to promote behavioral changes in transport users offer great potential to generate learning that is useful for the public and private actors involved.

scholarly journals Object detection and tracking in video sequences: formalization, metrics and results

Informatics ◽  
2021 ◽  
Vol 18 (1) ◽  
pp. 43-60
Author(s):  
R. P. Bohush ◽  
S. V. Ablameyko
Keyword(s):  
Moving Objects ◽  
Human Movement ◽  
Video Sequences ◽  
Multiple Objects ◽  
Movement Trajectories ◽  
Detection And Tracking ◽  
Form Features ◽  
One And Many ◽  
Tracking Objects

One of the promising areas of development and implementation of artificial intelligence is the automatic detection and tracking of moving objects in video sequence. The paper presents a formalization of the detection and tracking of one and many objects in video. The following metrics are considered: the quality of detection of tracked objects, the accuracy of determining the location of the object in a frame, the trajectory of movement, the accuracy of tracking multiple objects. Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. Neural network features are included in a composite descriptor that also contains geometric and color features to describe each detected person in the frame. The results of experiments based on the considered criteria are presented, and it is experimentally confirmed that the improvement of the detector operation makes it possible to increase the accuracy of tracking objects. Examples of frames of processed video sequences with visualization of human movement trajectories are presented.

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