Surveillance Camera System Research Articles

An Effective Interest Identification Technique to Enhance Sales Performance in Supermarkets

Surveillance Camera System is installed in the supermarkets mainly for security purposes. But the main idea of this paper is to use this surveillance camera system to improve the sales performance by targeting a particular stimulus (child) through marketing promotions. The owner of the supermarket monitors the entire store with the help of the security camera system. The owner suddenly finds an abnormal action in a stimulus (child) on looking at a particular product. On observation of the stimulus head and arm movements, the owner concludes the stimulus interest on that product which the parents refuse to buy. This scenario is implemented in this paper using live video analytics which identifies the abnormality. Action recognition is a technique that is used in the classification of actions present in the given video. The Bag of Visual Words Model is implemented for recognizing the action made by the stimulus. This model includes feature extraction, codebook generation and classification. The features from the stimulus such as arm and head are extracted using Speeded up Robust Features (SURF) algorithm. Codebook generation is done by K-means clustering and the histogram of discriminative features is generated and fed as input to SVM classifier which recognizes the action made by the stimulus (child) in order to identify the child’s interest factor on a particular product.

Optimal face templates: the next step in surveillance face recognition

The paper deals with surveillance face recognition in security applications such as surveillance camera systems or access control systems. Presented research is focused on enhancing recognition performance, reducing classification time and memory requirements. We aim to make it feasible to implement face recognition in end devices such as cameras, identification terminals or popular IoT devices. Therefore, we utilize algorithms that require low computational power and optimize them in order to reach higher recognition rates. We present a novel higher quantile method that enhances recognition performance via creation of robust and representative face templates for nearest neighbor classifier. Templates computed by the higher quantile method are determined by tolerance intervals which handle feature variability caused by face pose, expression, illumination and possible low image quality. The recognition performance evaluation has been conducted on images captured by surveillance camera system that are contained in unique IFaViD dataset. The IFaViD is the only one dataset captured by real surveillance camera system containing complex scenarios. The results show that the higher quantile method outperforms the contemporary approaches by 4%, respectively, 10% depending on the IFaViD’s test subset.

IoT Based Thermal Surveillance and Security System

Security is the need in day to day life. Use of intruder detection systems were increasing year by year. IR surveillance method for the detection of illegal intruder in low light condition is more easy unlike optical camera systems. This paper presents the design and implementation of intruder detection using IR sensor based system for application in the field of security and surveillance. Presenting methods are based on use of IR thermal detection system for the intruder detection, recognition and alerting. The use of such systems has special significance in the context of security in the domain of timely detection of abnormal movements inside the buildings. IR thermal imaging has higher advantages compared to optical camera surveillance systems because thermal imaging is effected by to weather conditions and can be used any time in a day. Presenting system are mainly used for illegal intruder detection inside buildings as well as infrared thermal imagers mounted on autonomous vehicles and unmanned aerial vehicles (UAV) and Banking Security Systems for intruder detection. Thermal sensors are used to detect the hot body by IR radiation detection. Thermal sensors are combined with microwave motion detection sensors to detect abnormal movement of hot bodies. Motion sensors also helps in prevention of false alarm due to external environmental condition. After detection of intruder alert the user using IoT systems.

Surveillance system with motion and face detection using histograms of oriented gradients

<span>With the rapidly increasing crime rate in recent years, community safety issues aroused a wide concern among public community. Various security technologies had been invented and carried out, for example password door lock, alarm system, and closed-circuit televisions (CCTVs). Although the installation of CCTVs is common in most premises, they require extensive man power to manually monitor the videos. Moreover, the reliability of human operator greatly deteriorates when they are in fatigue condition. In view of this, our project aims to develop an automated computer vision based surveillance system. Unlike ordinary CCTV system that requires human operator to manually observe and detect intruder, a computer vision based surveillance system automatically monitor the security of premises and trigger actions once an intrusion is detected. Basically, it is a simple surveillance camera system that will be setup at the entrance of the house. The reliability is being enhanced by applying the motion detection and face recognition algorithm, using histogram of oriented gradients that could detect the existence of people at the main entrance and try to validate the user. Apart from recognizing the user, the propose system also support mobile interaction whereby user can monitor the camera, activate alarm, and even received notification when a stranger was being detected at the entrance of the house. By including such functionalities, proposed system had highly surpassed the existing surveillance system by not only support monitoring, but also try to recognize the people and inform the user at the exact moment when stranger detected, so that user could take immediate action about it, for example activating the alarm or report to police. The project was executed with expected outcome and objectives had been accomplished.</span>

TEKNOLOGI MOTION-BASED TRACKING UNTUK PENGEMBANGAN APLIKASI KEAMANAN


 The surveillance camera system is widely used by the public. The surveillance camera system used is usually a CCTV camera. In general, CCTV cameras can only record video. Security monitoring or monitoring by CCTV cameras can only be effective if there are operators who see the record directly on a monitor. Actually the surveillance camera system can be programmed to give a warning sign to the user. The surveillance camera used in this study is the IP camera. The camera is a camera that can be programmed to provide a notification to the user. By implementing motion-based tracking technology on the surveillance camera system can detect movement. Kalman filter is one of the motion-based tracking methods. Kalman filters can predict the movements recorded by the IP camera. The results of this study state that the surveillance camera system can provide notification messages to users via an android device when the surveillance camera records the movement of human objects.
 

Energy Efficient Camera Solution for Video Surveillance

Video surveillance is growing rapidly, new problems and issues are also coming into view which needs serious and urgent attention. Video surveillance system requires a beneficial energy efficient camera solution. In this paper, a single overhead camera solution is introduced which overcomes the problems ex-isting in various frontal and overhead based surveillance systems. This will increases the efficiency and accuracy of surveillance system i.e. frontal and overhead. In this paper, two energy efficient overhead camera models are presented. The first model consists of a single overhead camera with a wide angle lens which covers a wide field of view addresses problems present in the traditional surveillance system. The second model, presents a single smart centralized overhead camera which controls various frontal based cameras. Several factors associated with camera models such as field of view, focal length and distortion are also discussed. Impact of the surveillance cameras are finally discussed which shows that a single energy efficient overhead camera surveillance system can solves many problems present in traditional surveillance system like power consumption, storage, time, human resource and installation cost and small coverage area.

Domain Adaptation and Adaptive Information Fusion for Object Detection on Foggy Days.

Foggy days pose many difficulties for outdoor camera surveillance systems. On foggy days, the optical attenuation and scattering effects of the medium significantly distort and degenerate the scene radiation, making it noisy and indistinguishable. Aiming to solve this problem, in this paper we propose a novel object detection method that has the ability to exploit the information in the color and depth domains. To prevent the error propagation problem, we clean the depth information before the training process and remove false samples from the database. A domain adaptation strategy is employed to adaptively fuse the decisions obtained in the color and depth domains. In the experiments, we evaluate the contribution of the depth information for object detection on foggy days. Moreover, the advantages of the multiple-domain adaptation strategy are experimentally demonstrated via comparison with other methods.

Authenticating Video Feeds using Electric Network Frequency Estimation at the Edge

Large scale Internet of Video Things (IoVT) supports situation awareness for smart cities; however, the rapid development in artificial intelligence (AI) technologies enables fake video/audio streams and doctored images to fool smart city security operators. Authenticating visual/audio feeds becomes essential for safety and security, from which an Electric Network Frequency (ENF) signal collected from the power grid is a prominent authentication mechanism. This paper proposes an ENF-based Video Authentication method using steady Superpixels (EVAS). Video superpixels group the pixels with uniform intensities and textures to eliminate the impacts from the fluctuations in the ENF estimation. An extensive experimental study validated the effectiveness of the EVAS system. Aiming at the environments with interconnected surveillance camera systems at the edge powered by an electricity grid, the proposed EVAS system achieved the design goal of detecting dissimilarities in the image sequences.

Convolutional Neural Network-Based Shadow Detection in Images Using Visible Light Camera Sensor.

Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detect and recognize the exact human area. Near-infrared (NIR) light cameras and thermal cameras are used to mitigate this problem. However, such instruments require a separate NIR illuminator, or are prohibitively expensive. Existing research on shadow detection in images captured by visible light cameras have utilized object and shadow color features for detection. Unfortunately, various environmental factors such as illumination change and brightness of background cause detection to be a difficult task. To overcome this problem, we propose a convolutional neural network-based shadow detection method. Experimental results with a database built from various outdoor surveillance camera environments, and from the context-aware vision using image-based active recognition (CAVIAR) open database, show that our method outperforms previous works.

A Proposed Design for Illumination and Cameras Surveillance System for Optimum Supervision at a Perimeter Area of Nuclear Facility

An important component of a comprehensive security plan is lighting. Security Protective Lighting has three functional objectives: To illuminate a person, object, place or condition of security to permit observation and identification, to be a physical deterrent through the glare effect of direct light on the human eye and to be a psychological deterrent creating in an intruder's mind the awareness that he or she will be discovered and observed during any unauthorized entry attempt. The most obvious reason for protective lighting is to make certain any person, object, place or condition will be sufficiently illuminated to provide effective security in a given region. Where perimeter lighting is required, the lighting units for a perimeter fence should be located a sufficient distance within the protected area and above the fence so that the light pattern on the ground will include an area both inside and outside the fence. Perimeter lighting should be continuous and on both sides of the perimeter fence and should be sufficient to support CCTV and other surveillance equipment where required. The cone of illumination from lighting units should be directed downward and outward from the structure or area being protected. The lighting should be arranged so as to create minimal shadows and minimal glare in the eyes of security guards. In this study a proposed design for security lighting and cameras surveillance system for optimum supervision at a perimeter area of a hypothetical nuclear facility will be presented. The illumination poles, lamps type, towers space distance, average and minimum Lighting Levels and Tilt Angle, required for camera surveillance system will be computed and determined. The work provides the requirements of cameras surveillance system at nuclear reactors isolation zone. Width of images sensitive area, lens focal length, lens format and angel of view will be determined by calculation method. The work determines cameras type, distributions, camera’s parameters and formulas according to the physical protection design process. Cameras angles of view, Lens Format, Lens focal length, F-Number and angle of view will be calculated. The optimum designing results for the security lighting (35 poles with 250 watt high pressure sodium and 34 m poles span with minimum lighting level equal 7 lux. The optimum CCTV design resulting in 15 cameras with length format 0.25 inch, length focal length 50 mm, F-stop number 1.8, angle of view 5.26 degree. In the future work; designers should consider the natural properties of reflectance, light absorption capacity, mobility and an object's inherent sensitivity to light to be sufficient to support CCTV system.

2016 UEFA European Championship: Pass and shot association

The purpose of this study is to analyze the association between technical features such as goal, pass, shot, ball possession and ball stealing and the goals scored in matches played by teams who qualified out of the group (n=16) and who could not (n=8) in 2016 UEFA European Championship. The data of the study were obtained by using computerized multiple camera surveillance system (Prozone). SPSS 22.0 program was used for the statistical analyses of this study. Independent T test was used to compare the parameters of teams who qualified out of the team and those who could not, while Pearson correlation analysis was used to analyze the association between variables. When the total shot parameters per match apart from shots, total pass, total pass to the third zone and ball stealing total data were compared, significant difference was found (p<0.05). In all of the shot parameters, especially in total goals scored and total shots on target (r=0.903), a positive high association was found in total ball stealing (r=0.796), total pass (r=0.753), total forward pass (r=0.819) and total pass to the third zone (r=0.748), while a negative intermediate association was found in average pass length per match (34+M) (r=-0.449). When the results were examined, it can be said that the teams who qualified out of the game can use technical properties effectively. It can be stated that in order to be successful in elite tournaments in the world, analysis practices should be taken more into consideration as well as technical and tactical practices.

Nghiên cứu ứng dụng kỹ thuật theo dõi đối tượng xây dựng hệ thống camera giám sát thông minh

This paper presents some results of building intelligent surveillance camera systems using object tracking. Main steps of the object tracker include (i) keypoint tracking using optical flow, (ii) keypoint matching, and (iii) consensus-base voting. A novel algorithm to accelerate processing using pipeline technique on multicores systems has also been proposed. The algorithm divides the whole processing frame into 4 stages which are executed on 4 different threads. Synchronization of threads is realized producer – consumer model. The proposed method achieved a 3.3 times increased computational time compared to the original one. The surveillance system continuously tracks target object and gives a warning sound if the object disappears in a predefined interval. Experimental results show that the proposed method achieves very promising results.

A FRAGILIZAÇÃO DOS ESPAÇOS PÚBLICOS A PARTIR DA UTILIZAÇÃO DE CÂMERAS DE VIGILÂNCIA NA CIDADE DE VILA VELHA (ES)

doi: 10.12957/geouerj.2016.16928 This article approaches the weakening of public spaces in a context of surveillance camera use, which will be discussed based on a case-study of Vila Velha surveillance camera system, a city located in the Metropolitan Area of Vitoria, Espirito Santo, Brazil. This investigation aims at deconstructing the public administration discourse, in which cameras are justifiable to combat crime and/or increase the feeling of safety among citizens. The study also aims at showing the damage caused to some of the conditions underlying the notion of public spaces if cameras are seen as technological devices that play the role of controlling social subjects and their spaces. We adopted participant observation behind the cameras to follow the work routine of camera operators and their workplace, as well as in front of the cameras to observe the everyday life in three monitored areas, interviewing passersby, residents and business owners. The results show some factors that limit the surveillance operation; the apparent indifference in which citizens relate to the cameras; and the weakening of public spaces, since cameras pose serious threats to liberty, plurality, and routine of citizens.

Broken Integrity Detection of Video Files in Video Event Data Recorders

As digital evidence has a highly influential role in proving the innocence of suspects, methods for integrity verification of such digital evidence have become essential in the digital forensic field. Most surveillance camera systems are not equipped with proper built-in integrity protection functions. Because digital forgery techniques are becoming increasingly sophisticated, manually determining whether digital content has been falsified is becoming extremely difficult for investigators. Hence, systematic approaches to forensic integrity verification are essential for ascertaining truth or falsehood. We propose an integrity determination method that utilizes the structure of the video content in a Video Event Data Recorder (VEDR). The proposed method identifies the difference in frame index fields between a forged file and an original file. Experiments conducted using real VEDRs in the market and video files forged by a video editing tool demonstrate that the proposed integrity verification scheme can detect broken integrity in video content.

Noisy vehicle surveillance camera: A system to deter noisy vehicle in smart city

With the increase in urbanization in modern cities, major roads and highways are built nearer to residential areas. Due to some inconsiderate driving behaviors, like accelerating and racing; illegal tailpipe modification; and aging vehicles, traffic noise is creating a nuisance to residents staying near highway, especially during late night or early morning. Unfortunately, these noisy vehicles often cannot be caught on the spot, unless traffic police is stationed at a certain place with their sound pressure level meter and camera. This latter approach is often not sustainable and incurs costly manpower resource. An automatic Noisy vehicle surveillance Camera (NoivelCam) system, which can be deployed in overhead structure across major highways near residential buildings, is being designed to capture noise level generated from passing vehicles and triggers a high-speed camera to capture the number plate of offending vehicles that exceed a certain noise level. Therefore, the proposed system provides time stamp, number plate, sound pressure level, audio, and video evidence of the offending vehicle and a means to issue an inspection notice to the owner of the vehicle. This paper provides a description of the NoivelCam, and some of its features to pinpoint noise generated from passing vehicle. An initial in-situ deployment of this system has been carried out in Singapore to test out its effectiveness in monitoring vehicle noise pressure level in a single lane on a highway.

Physical Activity and Gastric Residuals as Biomarkers for Region-Specific NEC Lesions in Preterm Neonates

Background: Necrotizing enterocolitis (NEC) is a serious feeding-related inflammatory gut disease with high mortality. Early clinical markers of NEC are of great importance for optimizing preventive interventions. Objective: Using preterm pigs as models, we hypothesized that an early postnatal onset of NEC can be predicted by decreased physical activity during the first few days after birth. Methods: Cesarean-delivered preterm pigs were fed parenteral nutrition and increasing amounts of formula for 5 days after birth (n = 120). Their physical activity was quantified by a continuous camera surveillance system and they were evaluated twice daily for clinical signs of apathy, discoloration, respiratory distress, abdominal distension and diarrhea. The volume of gastric residuals and the presence of macroscopic NEC-like lesions in the stomach, intestine and colon were recorded at euthanasia on day 5. Results: Half of the pigs (48%) showed clear NEC-like lesions on day 5, and these individuals had more adverse clinical symptoms from day 3 but decreased physical activity already from day 2 relative to the unaffected pigs (both p < 0.05). Only animals with NEC lesions in the small intestine had lower physical activity on days 2 and 3, and the increased volume of gastric residuals was specifically related to colon lesions (both p < 0.05). Conclusions: Decreased physical activity precedes the clinical symptoms of NEC in the small intestine of preterm pigs, and increased gastric residuals predict NEC lesions in the colon. Physical activity and gastric residuals may function as clinical biomarkers for region-specific NEC lesions in preterm neonates.

Abuse Prevention of Street Camera Network by Browsing-History Disclosure

A street camera network, in which many street cameras are installed at a high density, similar to street lights throughout a nation, will have a stronger positive effect in suspect tracking and crime deterrence in the near future. On the other hand, it will also have a stronger negative effect related to the violation of privacy of ordinary citizens. In order to make such a stronger surveillance camera system, which forcibly captures the images of passersby for the public interest, be accepted as an essential social infrastructure by a society, it is necessary for this camera system to make ordinary citizens be convinced that it is used only for the public interest. To realize this, a new concept, in which the abuse of a street camera network is deterred by browsing-history disclosure, is proposed.

Fire Detection Using Multi Criteria Image Processing Technique in Video Sequences

Vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. This paper proposes a multi criterion method to detect fire or flames by processing the video data generated by a high speed camera. Since flame images are special class of images, some of the unique features of a flame may be used to identify flame. There are some differences between flame images and other general images. By using these features we are able to detect fire correctly with least false alarm. In this paper we present an algorithm which can detect fire and reduce number of false alarms by counting number of identified pixels. In the algorithm, we preprocess the images to have better results. So first we adjust the gray level of a flame image according to its statistical distribution to have better processing. After that we try to extract fire features in images. First by using color characteristics, the ratio of red to green, we can identify probable fire-like or fire like pixels. Second, to highlight the regions with high gray level contrast at their edges, we use the extended prewitt filter. We use AND operation on two above processing images to remove unrelated pixels, at last by using flicker frequency, the oscillating change in the number of identified pixels over time is transformed into the frequency domain to complete detection algorithm. Simulation proves the algorithm ability to detect fire in different situations in video sequences.

Fire Detection Using Multi Criteria Image Processing Technique in Video Sequences

Vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. This paper proposes a multi criterion method to detect fire or flames by processing the video data generated by a high speed camera. Since flame images are special class of images, some of the unique features of a flame may be used to identify flame. There are some differences between flame images and other general images. By using these features we are able to detect fire correctly with least false alarm. In this paper we present an algorithm which can detect fire and reduce number of false alarms by counting number of identified pixels. In the algorithm, we preprocess the images to have better results. So first we adjust the gray level of a flame image according to its statistical distribution to have better processing. After that we try to extract fire features in images. First by using color characteristics, the ratio of red to green, we can identify probable fire-like or fire like pixels. Second, to highlight the regions with high gray level contrast at their edges, we use the extended prewitt filter. We use AND operation on two above processing images to remove unrelated pixels, at last by using flicker frequency, the oscillating change in the number of identified pixels over time is transformed into the frequency domain to complete detection algorithm. Simulation proves the algorithm ability to detect fire in different situations in video sequences.

Evaluation of Moving Object Detection Methods based on General Purpose Single Board Computer

RGA and SKDA are two different methods which can be used to detect the object in image based processing. In order to support the moving surveillance camera system which proposed in Telkom University, RGA and SKDA have tested to be reviewed which more reliable to be implemented in a single board computer. In this paper, will be discussed about implementation and testing of two different methods of object detection using backgrounds subtraction. For implementation, each of them will be combined with Extended Kalman Filter in a Raspberry Pi. The parameter which have tested are memory and CPU usage, and system utilization. The result shows that RGA is more reliable than SKDA to implemented in SBC because of less CPU usage and system utilization. DOI: http://dx.doi.org/10.11591/telkomnika.v14i1.7257