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Motion detection from video is a hot topic in computer vision. Also it is an important part of smart video surveillance system. In today's world surveillance system is playing an important role in the field of security. Moving object detection has been widely used in video surveillance systems. Besides, correct detection of moving objects is important part of video processing and surveillance systems...
In this paper a controller for PTZ cameras based on an unsupervised neural network model is presented. It takes advantage of the foreground mask generated by a non-parametric foreground detection subsystem. Thus, our aim is to optimize the movements of the PTZ camera to attain the maximum coverage of the observed scene in presence of moving objects. A growing neural gas (GNG) is applied to enhance...
Surveillance is becoming more and more important in the recent years. In many cities, cameras have been set to look after parks, streets, roads, facilities and so on, however this fact is rising concerns about privacy. In this work, an alternative surveillance method which gather at once security and privacy has been propose and tested. Based on fiber optic specklegram technology; a system consisting...
Car automation and surveillance is an escalating trend in this decade. Smart Vehicle security is becoming an indispensable need as it makes it easier for the owners to ensure their automobile's safety wirelessly. The core elements in our system consists of a mini central processing unit, motion detecting sensor accompanied with a camera module and buzzer. Our security network can be used to monitor...
We present a prototype for remote surveillance aiming at reducing the bandwidth requirements without compromising the reliability. The system consists of a network of off-the-shelf proximity sensors and a point-tilt-zoom (PTZ) camera. The camera captures video when an interrupt is received by one of the sensors. A remote server controls the operation of sensors and the camera, and is capable of receiving...
In recent years, designing and testing video anomaly detection methods have focused on synthetic or unrealistic sequences. This has mainly four drawbacks: 1) events are controlled and predictable because they are usually performed by actors; 2) environmental conditions, e.g. camera motion and illumination, are usually ideal thus realistic conditions are not well reflected; 3) events are usually short...
Camera networks have become more predominant in many aspects around our society. Designing active Pan-Tilt-Zoom (PTZ) camera networks requires placing the cameras appropriately in the environment according to the designated coverage requirements as well as examining the network's operational resilience to the environment dynamics. This design process is crucial before physically establishing the network...
This paper proposes a dataset and algorithms for pedestrian detection in UAVs. The method proposed is a HAARLBP based cascade classifier combined with saliency maps for improving the performance of the detector. In addition we introduce a dataset with images from surveillance cameras at different angles and altitudes emulating a UAV. We validate our dataset by the implementation of HOG algorithm and...
Moving target detection and tracking, recognition, behaviours analysis are the key issues in the intelligent visual surveillance system (IVSS). The challenge is how to process the real-time video stream in an effective way in case that we could find the interested objects for analysis. However, the traditional video surveillance technology often does not meet the needs of real-time key frame recognition...
Our objective is to count objects using a single frame from a surveillance camera. We focus on the area where individual object detectors fail, mostly due to clutter, occlusion, or variations in scene due to perspective change. For tackling the counting problem, first the object density is estimated by using ridge regression. Object counts are then estimated by integrating the density over the region...
In this paper, a new proposed model has been used to recognize human actions from video frames using a 3D deep neural network (3D DNN). To classify human actions, our recognition process is implemented under different recording conditions from a surveillance camera. By applying Caffe_GoogLeNet framework, we trained our 3D DNN with different training epoch values (TEs). The experiments were then evaluated...
In this paper, we propose a video-based indoor positioning system (VIPS) to provide centimeter-grade localization for the Internet of Things (IoT). The VIPS system integrates installed surveillance cameras with the IoT to provide highly-accurate positioning information to indoor people, which efficiently enables microlocation-aware IoT applications and services in smart environments. VIPS can estimate...
Action recognition has received increasing attention from the computer vision and machine learning communities in the last decade. To enable the study of this problem, there exist a vast number of action datasets, which are recorded under controlled laboratory settings, real-world surveillance environments, or crawled from the Internet. Apart from the "in-the-wild" datasets, the training...
In today's world data represented in the form of a video are prolific and has increased the requisite of storage devices unconditionally. These video sets takes up a huge space for amassing data and takes a long time to ascertain the content that requires a higher cognitive process for content search and retrieval. The efficient method for storing video data is to remove high-degree redundancies and...
With the dawn of rising sophisticated technology where everything or rather everyone depends on smartphones, tablets and voice assistants. With such increase in the rate of people using technology to automate their tasks, it is impractical to hire a person for monitoring the CCTV or the IP camera feed for the intruders. Hence, the concept of automation can be implemented here as well. CCTV cameras...
In recent years, vision based technologies have gained immense attention across academia-industries to enable optimal surveillance solution for event monitoring, analysis and control. However, the complexities of real time environment and expected functional characteristics often put question over existing approaches and their efficacy. In this paper, a number of the existing approaches for vision...
In this paper we explore detection of unusual activities using Markov Logic Network (MLN) based approach. Any human activity which is in variance from a defined usual set attracts human attention and is considered unusual. Such activities include anomaly detection in crowds, some repetition or omission of subactivities in a given sequence of activities in Ambient Assisted Living environments or an...
The use of infrared (IR) imaging to view scenes otherwise invisible to the human eye, simultaneously with visible-spectrum imaging, is increasingly of interest for various applications for such as in-vehicle, surveillance, and agricultural security cameras. The loss of spatial resolution in conventional RGB-IR sensors causes aliasing, because IR pixels are segmented within the provided effective pixel...
Moving objects detection or change detection in video sequences, is a fundamental task in video surveillance applications. Although, existing methods perform well on videos filmed by stationary cameras, these methods fail dramatically in videos filmed by non-stationary cameras. In particular, in very low frame rate and sudden illumination change scenarios, like Wide-Area Motion Imagery (WAMI). In...
Recently there has been a tremendous increase in the interest of the security of people and due to the ubiquitous presence of surveillance cameras and other similar systems, Automated surveillance systems have garnered widespread interest from the scientific community. Concomitantly, several advancements in the domain of biometrics have contributed to its pervasiveness in unrestricted environments...
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