Efficient Human Motion Detection with Adaptive Background for Vision-Based Security System

Motion detection is very important in video surveillance system especially for video compression, human detection and behaviour analysis. Various approaches have been used for detecting motion in a continuous video stream but for real-time video surveillance system, we need a motion detection that can provide accurate detection even in non-static background regardless of surroundings (outdoor or indoor), object speed and size, robust to camera noisy pixels or sudden change in light intensity. This is very important to ensure that the security of a monitored parameter or area is not compromised. In this paper, we propose a method for human motion detection which employs adaptive background subtraction, camera noise reduction and white pixel counts threshold for real-time video streams

Efficient human motion detection with adaptive background for vision-based security system

Motion detection is very important in video surveillance system especially for video compression, human detection, and behaviour analysis. Various approaches have been used for detecting motion in a continuous video stream but for real-time video surveillance system; we need a motion detection that can provide accurate detection even in non-static background regardless of surroundings (outdoor or indoor), object speed and size, robust to camera noisy pixels or sudden change in light intensity. This is very important to ensure that the security of a monitored parameter or area is not compromised. In this paper, we propose a method for human motion detection that employs adaptive background subtraction, camera noise reduction and white pixel count threshold for real-time video streams

Automatic human face detection for home surveillance application

This paper concentrates on exploiting human face informa tion for surveillance applications in a home environment. The system features real-time human face detection and facial feature identification. It is our aim to insert the results in a video-security system architec ture, where MPEG-4 coding techniques enable low bit-rate video trans mission over a home network environment. The processing contains the following essential elements: (1) skin-color segmentation, (2) histogram analysis for facial feature detection, and (3) probability-based confidence value evaluation of facial features. We have tested our sequence of pro cessing algorithms on a set of video sequences. The experimental results show that our approach offers near real-time processing speed with good detection capability, but the robustness needs further improvement

Automatic human face detection for home surveillance application

This paper concentrates on exploiting human face informa tion for surveillance applications in a home environment. The system features real-time human face detection and facial feature identification. It is our aim to insert the results in a video-security system architec ture, where MPEG-4 coding techniques enable low bit-rate video trans mission over a home network environment. The processing contains the following essential elements: (1) skin-color segmentation, (2) histogram analysis for facial feature detection, and (3) probability-based confidence value evaluation of facial features. We have tested our sequence of pro cessing algorithms on a set of video sequences. The experimental results show that our approach offers near real-time processing speed with good detection capability, but the robustness needs further improvement

Moving Object Detection and Tracking for Video Surveillance: A Review

This paper presents a review and systematic study on the moving object detection and surveillance of the video as it is an important and challenging task in many computer vision applications, such as human detection, vehicles detection, threat, and security. Video surveillance is a dynamic environment, especially for human and vehicles and for specific object in case of security is one of the current challenging research topics in computer vision. It is a key technology to fight against terrorism, crime, public safety and for efficient management of accidents and crime scene going on now days. The paper also presents the concept of real time implementation computing task in video surveillances system. In this review paper various methods are discussed were evaluation of order to access how well they can detect moving object in an outdoor/indoor section in real time situation

Recent Trends in Video Surveillance System in Dense Environment: - A Review Paper

Snow, fog, lightning, torrential rain, and darkness degrade outdoor surveillance footage. The detection, categorization, and event/object recognition capabilities of video surveillance systems in congested environments have attracted considerable interest. Real-time video analysis algorithms in various weather conditions have been enhanced by technology. Other examples include background extraction, the see-through algorithm, deep learning models, CNN for nocturnal incursions, the system for high-quality underwater monitoring utilising optical-wireless video surveillance, LVENet, and edge computing. In the current study, these methodologies improved monitoring efficiency and decreased human error. This study details these video surveillance techniques, platforms, and supplementary materials. After discussing prevalent building and architectural styles briefly, significant system evaluations are presented. This study contrasts current surveillance systems with various methods for real-time video processing under challenging weather conditions in order to provide readers with a thorough understanding of the system. The following research is also highlighted