Video Monitoring Research Articles

Density-based one-shot active learning for image segmentation

Image segmentation is a key step in image processing tasks, which has significant applications in computer vision field such as medical image analysis, scene understanding and video monitoring, etc. However, image segmentation tasks usually require a large number of labeled samples to obtain great performance of convolutional neural networks (CNNs). Active learning (AL) can select valuable samples for annotation, so as to reduce the annotation cost as much as possible while maintaining the performance of CNNs. Further, one-shot AL can select valuable samples by once, which eliminates the need for iterative sample selection and annotation. However, existing one-shot AL approaches extremely rely on complex clustering algorithm, which brings a limitation in practice, i.e., we often do not know how to set the hyperparameters. In this paper, we propose a clustering-free one-shot AL framework, which is based on self-supervised feature learning and density-based query strategy. Our framework can select samples with high local density robustly against hyperparameters. The experimental results are impressive that state-of-the-art one-shot active learning performance can be achieved with simple density-based sampling.

The probability of achieving remission after correction of therapy in patients with pharmacoresistant focal epilepsy

Drug-resistant forms of epilepsy are an important medical and social problem.Goal of the work. Evaluation of the probability of achieving remission after correction of therapy in patients with drug-resistant focal epilepsy.Material and methods. The study included 309 patients divided into three heterogeneous groups: a group of patients with focal pharmacoresistant epilepsy; a group of patients with super refractory focal epilepsy; control group – patients who had not previously received treatment. The examination included history taking, clinical and neurological examination, routine EEG and/or EEG video monitoring, MRI of the brain, and analysis of medical records. Therapy was adjusted.Results. After correction of therapy, remission in patients in Group 1 was achieved in 27.8% of patients, improvement – in 27.1%, no effect – in 45.1%; in Group 2, remission was achieved in 13.2% of patients, improvement – in 28.6%, no effect – in 58.2%; in Group 3, remission was achieved in 41.2% of patients, improvement – in 32.9%, no effect – in 25.9%. Negative prognostic factors did not show a significant correlation with the lack of effect of therapy.Conclusion. After correction of therapy, remission was achieved in several patients with drug-resistant focal epilepsy, while negative prognostic factors do not exclude the possibility of achieving remission.

THE METHOD OF SEGMENTATION OF THE IMAGES IN THE REMOTE VIDEO MONITORING SYSTEM BASED ON THE K-MEANS ALGORITHM

The configuration of the video monitoring system, which is widely used in the protection systems of objects and positions of units, is given. Examples of the collision line video monitoring system are given, namely: the video monitoring system of the special monitoring mission of the Organization for Security and Cooperation in Europe and the battalion video surveillance complex. An analysis of known methods of image segmentation in video monitoring systems has been carried out. The analysis showed that these methods do not meet the requirements for the quality of image segmentation in the video monitoring system. The image segmentation method in the remote video monitoring system has been improved, in which, unlike the known ones: the source image is divided into RGB brightness channels; determination of the Euclidean distance between pixels; division of the entire set of image pixels into subsets; recalculation of “centers” of each subset; reassignment of new “centers” of each subset; minimization of total intra-cluster variance. Experimental studies of image segmentation from the remote video monitoring system were conducted. The image from the video monitoring system on the contact line during hostilities during the russian-ukrainian war is used as the source image. The segmentation results of this source image are given. It was established that there is a visual possibility of identifying objects of interest on segmented images. At the same time, it is possible to visually determine the elements of the protective cape only at k=4, while at k=2 and k=3 this possibility is complicated. The directions of further research are the determination of the optimal value of the value k when using the k-means algorithm and the evaluation of the quality of image segmentation in the remote video monitoring system.

Low recruitment drives the decline of red porgy (Pagrus pagrus) along the southeast USA Atlantic coast: Inferences from fishery-independent trap and video monitoring.

Red porgy (Pagrus pagrus) is a reef-associated, economically-important, winter-spawning, protogynous Sparidae species that appears to have declined in abundance in recent years along the southeast United States Atlantic coast. We used spatially-explicit generalized additive models built with fishery-independent chevron trap (1990-2021) and video data (2011-2021) to quantify the ways in which red porgy relative abundance and mean size varied across temporal, spatial, environmental, and habitat variables. Mean red porgy relative abundance from traps declined by 77% between 1992 and 2021, and declines were similarly large (69%) on video between 2011 and 2021. The largest two-year decline in relative abundance occurred early in the COVID-19 pandemic (2019-2021)- 32% in traps and 45% on video-despite already low abundance. Highest red porgy relative abundance from traps and video occurred in deep areas (i.e., 60-100 m) between southern North Carolina and north Georgia, and red porgy preferred low relief but continuous hardbottom habitats (i.e., pavement). We confirmed recent low recruitment of red porgy in the region based on the large increase in mean length (29%) and severe (~99%) declines of juvenile red porgy caught over the 32-year trap survey. Evidence suggests that recruitment failure is partially or mostly responsible for red porgy abundance declines, and, moreover, the regulation of harvest is unlikely to achieve sustainable management goals until recruitment increases.

On the Issue of Compliance with the Legislation on Personal Data by the Employer During Video Recording and Psychophysiological Study of Workers on the Polygraph

The article is devoted to the issues of compliance by the employer with the legislation of the Russian Federation on the collection of personal data of an employee through technical means of control over him and his workplace, as well as the fact and limits of interference in his private life. In this case, the need for the legitimacy of ensuring the rights and obligations of the parties to labor relations and the consistency of their interests is indicated. The authors note that the workplace is under the control of the employer, who is free to choose the means of control over the employee. The article discusses such means of control as video surveillance of employees and their testing on a polygraph (lie detector). An analysis of the current labor and other legislation of the Russian Federation, which regulates these legal relations of participants in the labor process, as well as the current judicial practice, which is ambiguous, has been undertaken. It is concluded that video surveillance and video recording of the workplace, subject to a number of conditions specified in the article, do not aim to interfere with the private life of the employee, do not violate the rules on the protection of personal data, since they are aimed at ensuring the safety of employees, their control, the safety of property on the territory of the employer, fixing and proving non-fulfillment by the employee of his labor duties. The article formulates a number of requirements, the observance of which will ensure the legality of video monitoring and the inadmissibility of violating the rights and freedoms of employees. When testing an employee on a polygraph, taking into account the provisions of the Labor Code of the Russian Federation, a polygraph examiner acting in the interests of the employer should also comply with the requirements of legislation on personal data. Compliance by the employer with certain conditions for the participation of an employee in a psychophysiological study using a polygraph, including bringing to the attention of the employee the subject and purpose of the study that are of interest to the employer, makes this event voluntary and legal, and the processing of personal data in the process of its implementation – in line with current legislation in the field of personal data and labor relations.

Practical Application of Body Mechanics Principles in the Process of Health Workers Doffing Personal Protective Equipment

To examine the application effect of body mechanics principles in the process of health workers doffing personal protective equipment (PPE). A total of 360 health workers from a Fangcang shelter hospital, also known as alternate care site, in Shanghai were involved in a centralized 1-day training concerning essential skills for taking off PPE. The training was focused on integrating body mechanics principles, including expanding the support surface, lowering the center of gravity, reducing the shift in the the center of gravity, using the principle of leverage, and creating the appropriate operating space, in the PPE doffing process. Through remote video monitoring and recording, observations were made of the physical stability, pollution risks, and operational smoothness of the health workers when they applied body mechanics principles in their actions. The results of binary logistic regression showed that, compared with the actions taken without applying body mechanics principles, performing the operation of the body leaning forward and then slightly leaning backward was positively correlated with stability in the doffing process (odds ratio [O R]=3.291, 95% confidence interval [ CI]: 1.627-6.656), negatively correlated with pollution risks ( OR=0.203, 95% CI: 0.100-0.412), and positively correlated with operational smoothness ( OR=20.847, 95% CI: 8.061-53.916); performing the operation of taking off the boot sleeve in a horse-riding stance, with one foot standing ahead of the other, was positively correlated with stability ( OR=5.299, 95% CI: 1.041-26.957), negatively correlated with pollution risks ( OR=0.079, 95% CI: 0.009-0.692), and positive correlated with operational smoothness ( OR=16.729, 95% CI: 1.238-226.077); performing the operation of taking off the boot sleeve by lifting the heel and then the toes was positively correlated with stability ( OR=19.361, 95% CI: 8.391-44.671), negatively correlated with pollution risks ( OR=0.181, 95% CI: 0.084-0.393), and positively correlated with operational smoothness ( OR=10.977, 95% CI: 3.764-32.008); performing the operation of the leaning forward and keeping the face looking forward when taking off the mask was positively correlated with stability ( OR=2.935, 95% CI: 1.412-6.101), negatively correlated with pollution risks ( OR=0.123, 95% CI: 0.059-0.258), and positively correlated with operational smoothness ( OR=18.126, 95% CI: 6.665-49.297). In the process of medical staffs doffing PPE, correct and proper mechanical postures and actions can effectively assist medical staffs to maintain balance and stability and reduce the risks of infection, which has major significance and should be widely incorporated in personal protection skills training and applied in clinical practice.

Assessing the Security and Privacy of Baby Monitor Apps

Emerging technologies in video monitoring solutions seriously threaten personal privacy, as current technologies hold the potential for total surveillance. These concerns apply in particular to baby monitor solutions incorporating mobile applications due to the potential privacy impact of combining sensitive video recordings with access to the vast amount of private data on a cell phone. Therefore, this study extends the state of privacy research by assessing the security and privacy of popular baby monitor apps. We analyze network security measures that aim to protect baby monitoring streams, evaluate the corresponding privacy policies, and identify privacy leaks by performing network traffic analysis. Our results point to several problems that may compromise user privacy. We conclude that our methods can support the evaluation of the security and privacy of video surveillance solutions and discuss how to improve the protection of user data.

Novel interventions significantly reduce falls with fractures: A meta-analysis and systematic review

IntroductionWorldwide, falls lead to possible complications such as prolonged hospitalization, prolonged bed rest, pressure injuries, fractures and mortality. AimsThe study aimed to evaluate the effectiveness of novel fall prevention strategies that utilized technology in preventing falls. MethodsThe meta–analysis and systematic review was guided by the Cochrane guidelines for systematic reviews of interventions. The authors searched databases for specified keywords. ResultsA total of 22 studies were included. Interventions included multi-modal fall prevention interventions, camera surveillance, motion sensors and bed/chair exit alarms. Video monitoring was equivocal in reducing fall rates. Exit alarms statistically significantly reduce falls between groups but not within groups. The interventions were not statistically significant in reducing falls with minor injuries but they were statistically significant in reducing falls with serious injuries including fractures. ConclusionA comprehensive fall prevention care plan, rather than one specific intervention, is necessary to prevent falls effectively.

EVALUATION OF CHEMISTRY LEARNING VIDEOS FROM ONLINE LEARNING APPLICATIONS IN INDONESIA

E-learning is not distinct from the use of technology, which includes a variety of digital platforms. Zenius, Ruangguru, Pahamify, and other online learning systems are currently available in Indonesia. There are various learning films on the learning platform, such as on the applications B and C, which both give a variety of features and materials that complement the curriculum K-13, particularly in chemistry. The qualitative descriptive methodologies were used in this investigation. The purpose of this research is to compare the quality of chemistry learning resources available on online learning applications that correspond to the 2013 curriculum. Data is gathered through the downloading and video monitoring of chemical compounds. Two learning apps, B and C, were utilized as examples. According to the findings of this study, application B has a bigger number of videos in the material than application C. In addition, the average video time on the B app is less topical than on the C app. A good learning video has an appropriate length. When the video is too long, the spectator becomes bored. The video's attributes should be clear, and a pleasant appearance, such as animation, can encourage students to follow.

A framework for airborne infection risk assessment based on real-time occupant distribution prediction in outpatient waiting space

Outpatient waiting space (OWS) is a place with high risks of cross-infection and epidemic transmission of infectious respiratory diseases in hospitals. The dynamic changes of occupant distribution in OWS significantly increase the uncertainty of its infection risk assessment. Therefore, this study aims to develop an integrated framework for airborne infection risk assessment based on real-time occupant distribution prediction in OWS. The proposed framework included four steps. First, the consultation data and monitoring video data were collected from the consultation service system and monitoring videos. Second, difference analysis and correlation analysis were performed to identify the feature variables from the collected data for predicting occupant number (OPN) and their dwell time (DT) in OWS. Third, different machine learning (ML) models were trained using the extracted feature variables to select the model with the best prediction performance. Finally, based on the predicted OPN and DT, the real-time airborne infection risk was calculated. A typical children's hospital was selected to verify the proposed framework in 10 OWSs of different departments. The results showed that the average prediction accuracy for OPN and DT was 73.31% and 72.66%, respectively. The infection probability calculated based on the predicted occupant distribution was close to the actual values with a mean absolute error of 0.27, and its accuracy was improved by 64.9% compared with the calculation results using standard OPN and fixed DT. Furthermore, the application of this framework could reduce the ventilation rate by 11.36% compared with that using fixed ventilation according to the existing standards.

Assimilation of peak period from video images in numerical wave models at a local scale

This paper presents an innovative methodology to assimilate peak period into wave models at a local scale. The proposed methodology estimates the peak period by processing time stack images from a video monitoring system for assimilation into a wave energy balance spectral model. Assimilation of the wave peak period is performed by correcting the boundary conditions and replacing the directional spectra prescribed by SWAN when using a nesting scheme. This methodology represents a new procedure for assimilating wave peak periods in coastal areas with video system infrastructures. The wave modelling is performed using a three-mesh nesting scheme where the finer domain coincides with the local scale and the proposed assimilation methodology is applied. The results show that the model improves the estimation of the peak period across the whole domain. The shape of the spectrum obtained changes significantly in the inner domain, mainly for low frequencies.

Application of SSD network algorithm in panoramic video image vehicle detection system

Abstract Due to the popularity of high-performance cameras and the development of computer video pattern recognition technology, intelligent video monitoring technology is widely used in all aspects of social life. It mainly includes the following: industrial control system uses video monitoring technology for remote monitoring and comprehensive monitoring; in addition, intelligent video monitoring technology is also widely used in the agricultural field, for example, farm administrators can view the activities of animals in real time through smart phones, and agricultural experts can predict future weather changes according to the growth of crops. In the implementation of intelligent monitoring system, automatic detection of vehicles in images is an important topic. The construction of China’s Intelligent Transportation System started late, especially in video traffic detection. Although there are many related studies on video traffic detection algorithms, these algorithms usually only analyze and process information from a single sensor. This article describes the application of the single-shot detector (SSD) network algorithm in a panoramic video image vehicle detection system. The purpose of this article is to investigate the effectiveness of the SSD network algorithm in a panoramic video image vehicle detection system. The experimental results show that the detection accuracy of a single convolutional neural network (CNN) algorithm is only 0.7554, the recall rate is 0.9052, and the comprehensive detection accuracy is 0.8235. The detection accuracy of SSD network algorithm is 0.8720, recall rate is 0.9397, and the comprehensive detection accuracy is 0.9046, which is higher than that of single CNN algorithm. Thus, the proposed SSD network algorithm is compared with a single convolution network algorithm. It is more suitable for vehicle detection, and it plays an important role in panoramic video image vehicle detection.

Effects of losartan and enalapril on lithium-pilocarpine-induced status epilepticus, spontaneous convulsive seizures, and cardiac changes in rats

Modulating the brain renin-angiotensin system presents an innovative pathway for exploring newer treatment approaches in epilepsy. The current study aimed to evaluate the influence of losartan (LOS) and enalapril (ENP), which are angiotensin receptor blocker and angiotensin-converting enzyme inhibitor, respectively, on the incidence, initiation, and duration of status epilepticus (SE), spontaneous convulsive seizures (SCS), survival, and cardiac alterations in rats subjected to lithium-pilocarpine (LiP)-induced SE. Lithium (127 mg/kg, i.p.) pretreated male Wistar rats were administered pilocarpine (30 mg/kg, i.p.) after 24 h to induce SE, which was terminated after 90 min of onset. Daily 10-h video monitoring was carried out for examining onset, frequency, duration of SCS, and mortality till 18 days. The administration of LOS (10 mg/kg, i.p.), ENP (20 mg/kg, i.p.) and atenolol (AT; 50 mg/kg, p.o.) was started before lithium in pre-SE protocol and for post-SE protocol these drugs were administered 1 h after terminating SE and continued for 7 days’ post-SE. Cardiac pathology, echocardiography, heart weight/body weight ratio, and histopathology were evaluated. None of the drugs used (LOS/ENP/AT) offered protection against SE. Administration before SE decreased and post-SE administration increased the latency of SCS, and the overall duration of seizures remained short in both cases as compared to untreated rats. The heart weight/body weight ratio decreased in rats that did not survive. No echocardiographic changes were observed in any of the groups. Untreated SE rats showed myocyte ischemic changes, which were not present in any treated rats. In conclusion, LOS may reduce cardiac complications in SE rats. Hence, further evaluation of LOS as an add-on in epilepsy treatment should be performed.

Users' Information Security Awareness of Home Closed-Circuit Television Surveillance

Closed-circuit television (CCTV) surveillance cameras are widely used in public and private areas around the world. It is primarily used for tracking individuals and preventing criminal activities. It is necessary to balance the benefits of video surveillance and the risks it poses to individuals' right to privacy. The existing studies raised privacy issues of installing CCTV in public places. However, there is a lack of studies investigating users’ awareness of information security and privacy limitations in installing CCTV in private places. Thus, in this study, the author evaluated users' information security awareness of the value of CCTV and other forms of video surveillance. In-person interviews were conducted in Riyadh province, Kingdom of Saudi Arabia. A total of 77 individuals responded to the interview. A qualitative analysis was conducted to evaluate the participants’ perception of CCTV usage. The outcome of the analysis revealed four themes: Privacy invasion, privacy awareness, dilemmas in implementing security, and preventive measures. The findings revealed that the participants required strict privacy policies for installing CCTV video monitoring systems in private areas. In addition, they understood that CCTV is effectively reducing the fear of crime. The research contributes to understanding users' general awareness of information security and offers the necessary steps to protect the user's privacy in a CCTV surveillance environment. In addition, a data-sharing framework is recommended to share the data in a secure environment. Furthermore, researchers can utilize the study findings in conducting further similar investigative studies.

An Improved CrowdDet Algorithm for Traffic Congestion Detection in Expressway Scenarios

Traffic congestion detection based on vehicle detection and tracking algorithms is one of the key technologies for intelligent transportation systems. However, in expressway surveillance scenarios, small vehicle size and vehicle occlusion present severe challenges for this method, including low vehicle detection accuracy and low traffic congestion detection accuracy. To address these challenges, this paper proposes an improved version of the CrowdDet algorithm by introducing the Involution operator and bi-directional feature pyramid network (BiFPN) module, which is called IBCDet. The proposed IBCDet module can achieve higher vehicle detection accuracy in expressway surveillance scenarios by enabling long-distance information interaction and multi-scale feature fusion. Additionally, a vehicle-tracking algorithm based on IBCDet is designed to calculate the running speed of vehicles, and it uses the average running speed to achieve traffic congestion detection according to the Chinese expressway level of serviceability (LoS) criteria. Adequate experiments are conducted on both the self-built Nanjing Raoyue expressway monitoring video dataset (NJRY) and the public dataset UA-DETRAC. The experimental results demonstrate that the proposed IBCDet outperforms the commonly used object detection algorithms in both vehicle detection accuracy and traffic congestion detection accuracy.

High-Precision Satellite Video Stabilization Method Based on ED-RANSAC Operator

Video image stabilization technology is a crucial foundation for applications such as video image target identification, monitoring, and tracking. Satellite video covers a wide range of areas with complex and similar types of objects on the ground and diverse video types. However, currently, there is a lack of a general high-precision satellite video stabilization method (VSM) that can be applied to different land cover types and imaging modes. This paper proposes a high-precision VSM based on the ED-RANSAC, an error elimination operator constrained by Euclidean distance. Furthermore, a set of accuracy evaluation methods to ensure the reliability of video stabilization are sorted out. This paper conducted video stabilization experiments using optical video data from the Jilin-01 satellite and airborne SAR video data. Under the precision evaluation criteria proposed in this paper, the optical satellite video achieved inter-frame stabilization accuracy of better than 0.15 pixels in different test areas. The overall stabilization accuracy was better than 0.15 pixels. Similarly, the SAR video achieved inter-frame stabilization accuracy better than 0.3 pixels, and the overall stabilization accuracy was better than 0.3 pixels. These experimental results demonstrate the reliability and effectiveness of the proposed method for multi-modal satellite video stabilization.

Prevalence of gastroesophageal reflux disease in children with extraesophageal manifestations using combined-video, multichannel intraluminal impedance-pH study

Gastroesophageal reflux disease (GERD) might be either a cause or comorbidity in children with extraesophageal problems especially as refractory respiratory symptoms, without any best methods or criterion for diagnosing it in children.To evaluate the prevalence of extraesophageal GERD using conventional and combined-video, multichannel intraluminal impedance-pH (MII-pH), and to propose novel diagnostic parameters.The study was conducted among children suspected of extraesophageal GERD at King Chulalongkorn Memorial Hospital between 2019 and 2022. The children underwent conventional and/or combined-video MII-pH. The potential parameters were assessed and receiver operating characteristic was used for the significant parameters.Of 51 patients (52.9% males), aged 2.24 years were recruited. The common problems were cough, recurrent pneumonia, and hypersecretion. Using MII-pH, 35.3% of the children were diagnosed with GERD by reflux index (31.4%), total reflux events (3.9%), and symptom indices (9.8%) with higher symptom recorded in the GERD group (94 vs 171, P = 0.033). In the video monitoring group (n = 17), there were more symptoms recorded (120 vs 220, P = 0.062) and more GERD (11.8% vs 29.4%, P = 0.398) by symptom indices. Longest reflux time and mean nocturnal baseline impedance were significant parameters for diagnosis with receiver operating characteristic areas of 0.907 (P = 0.001) and 0.726 (P = 0.014).The prevalence of extraesophageal GERD in children was not high as expected. The diagnostic yield of symptom indices increased using video monitoring. Long reflux time and mean nocturnal baseline impedance are novel parameters that should be integrated into the GERD diagnostic criteria in children.

Improving satellite monitoring of coastal inundations of pelagic Sargassum algae with wind and citizen science data

Massive blooms of pelagic Sargassum algae have caused serious problems to coastal communities and ecosystems throughout the tropical Atlantic, Caribbean Sea, and Gulf of Mexico since 2011. Efforts to monitor and predict these occurrences are challenging owing to the vast area impacted and the complexities associated with the proliferation and movement of Sargassum. Sargassum Inundation Reports (SIRs) were first produced in 2019 to estimate the potential risk to coastlines throughout the Intra-American Sea at weekly intervals at 10 km resolution. SIRs use satellite-based data products to estimate beaching risk from the amount of offshore Sargassum (quantified by a Floating Algal density index). Here we examine whether including wind metrics improves the correspondence between the offshore Floating Algal density index and observations of Sargassum along the coastline. For coastal observations, we quantified the percent coverage of Sargassum in photos obtained from the citizen science project "Sargassum Watch" that collects time-stamped, georeferenced photos at beaches throughout the region. Region-wide analyses indicate that including shoreward wind velocity with SIR risk indices greatly improves the correspondence with coastal observations of Sargassum beaching compared to SIR risk indices alone. Site-specific analyses of photos from southeast Florida, USA, and data from a continuous video monitoring study at Puerto Morelos, Mexico, suggest potential uncertainties in the suite of factors controlling Sargassum beaching. Nonetheless, the inclusion of wind velocity in the SIR algorithm appears to be a promising avenue for improving regional risk indices.

Simulation and Research of Railway Foreign Body Invasion System Based on Single Chip Microcomputer

With the accelerating growth of railway operating mileage in China, ensuring the safety of railway operations has become a critical problem. According to some previous studies, the railway foreign body invasion limit is a major threat to the safe operation of the railway. As the current stage mainly adopts the combination of manual inspection and video monitoring, it has some disadvantages, such as being time-consuming, laborious, and inefficient. Meanwhile, it cannot timely detect potential danger. Therefore, the research on the simulation of railway foreign body intrusion systems based on single-chip microcomputers is carried out. The program is compiled in C language and uses the microcontroller to achieve real-time foreign object detection and alarm for encroachment. This paper mainly introduces the principle of the system and uses Proteus software to design and simulate the circuit. Last but not least, welding is carried out according to the circuit diagram, and the physical test is carried out to verify the feasibility of the design.

Smart all-time vision: The battery-free video communication for urban administration and law enforcement

The Chinese government is dedicated to enhancing the level of informatization in administrative law enforcement to ensure fairness and increase credibility. Currently, law enforcement has exposed such problems as insufficient force, difficulties in collecting evidence, and low evidential power. These problems contradict the principles of rule of law and standardization. Many local governments have implemented advanced information technologies for urban administration and law enforcement, including big data, artificial intelligence, and IoT. Among these technologies, IoT is the core communication infrastructure for innovative law enforcement platforms. However, traditional video communications rely on batteries or dedicated power sources, leading to maintenance challenges and high power consumption. In this paper, we propose AT-Eye, a new video communication paradigm for all-time law enforcement video monitoring, which is battery-free and high-throughput. The key enabler of AT-Eye is ambient backscatter technology, which enables energy harvesting and video communication simultaneously. Unlike previous methods, our proposal introduces a novel CCK-based modulation for tag cameras and achieves 4-way concurrency. The modulation is simple because it uses phase difference and it is energy-efficient because generating square waves is adequate. Moreover, to ensure full compatibility with COTS WiFi, we modulate the physical service data unit. Therefore, data recovery is possible using only commercial NICs. We conduct comprehensive experiments to examine our proposal and experiment results show that AT-Eye achieves a throughput of 10.8 Mbps with COTS radios. We also simulate a 16-way battery-free tag camera system, demonstrating AT-Eye's feasibility of high-definition video communication.