SCface is a database of static images of human faces. Images were taken in uncontrolled indoor environment using five video surveillance cameras of various qualities. Database contains 4160 static images (in visible and infrared spectrum) of 130 subjects. Images from different quality cameras mimic the real-world conditions and enable robust face recognition algorithms testing, emphasizing different law enforcement and surveillance use case scenarios.

The Detection of Crime, Resource Deployment, and Predictors of Success: A Multi-Level Analysis of Closed-Circuit Television (CCTV) in Newark, NJ collection represents the findings of a multi-level analysis of the Newark, New Jersey Police Department's video surveillance system. This collection contains multiple quantitative data files (Datasets 1-14) as well as spatial data files (Dataset 15 and Dataset 16). The overall project was separated into three components: Component 1 (Dataset 1, Individual CCTV Detections and Calls-For-Service Data and Dataset 2, Weekly CCTV Detections in Newark Data) evaluates CCTV's ability to increase the "certainty of punishment" in target areas; Component 2 (Dataset 3, Overall Crime Incidents Data; Dataset 4, Auto Theft Incidents Data; Dataset 5, Property Crime Incidents Data; Dataset 6, Robbery Incidents Data; Dataset 7, Theft From Auto Incidents Data; Dataset 8, Violent Crime Incidents Data; Dataset 9, Attributes of CCTV Catchment Zones Data; Dataset 10, Attributes of CCTV Camera Viewsheds Data; and Dataset 15, Impact of Micro-Level Features Spatial Data) analyzes the context under which CCTV cameras best deter crime. Micro-level factors were grouped into five categories: environmental features, line-of-sight, camera design and enforcement activity (including both crime and arrests); and Component 3 (Dataset 11, Calls-for-service Occurring Within CCTV Scheme Catchment Zones During the Experimental Period Data; Dataset 12, Calls-for-service Occurring Within CCTV Schemes During the Experimental Period Data; Dataset 13, Targeted Surveillances Conducted by the Experimental Operators Data; Dataset 14, Weekly Surveillance Activity Data; and Dataset 16, Randomized Controlled Trial Spatial Data) was a randomized, controlled trial measuring the effects of coupling proactive CCTV monitoring with directed patrol units. Over 40 separate four-hour tours of duty, an additional camera operator was funded to monitor specific CCTV cameras in Newark. Two patrol units were dedicated solely to the operators and were tasked with exclusively responding to incidents of concern detected on the experimental cameras. Variables included throughout the datasets include police report and incident dates, crime type, disposition code, number of each type of incident that occurred in a viewshed precinct, number of CCTV detections that resulted in any police enforcement, and number of schools, retail stores, bars and public transit within the catchment zone.

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This multi-camera surveillance dataset, the SAIVT-SoftBio database, was captured from an existing surveillance network, to enable the evaluation of person recognition and re-identification models in a reallife multi-camera surveillance environment.

The dataset consists of 150 people moving through a building environment, recorded by eight surveillance cameras. Each camera captures data at 25 frames per second, at a resolution of 704 x 576 pixels, and is calibrated using Tsai’s method. The placement of cameras is a real-life surveillance setup, and cameras have been placed to provide maximal coverage of the space (with some overlap) and observation of the entrances to the building. The dataset was collected in an uncontrolled manner, so subjects can travel any route through the building. Thus, the vast majority of subjects will only pass through a subset of the camera network and that subset varies from person to person. This provides a highly unconstrained environment in which to test person re-identification models.

The frames are recorded from when the subject enters the building through one of the three main doorways visible in Camera 4, Camera 7 and Camera 5/8, until they leave observation either through exiting the building or entering a lecture theatre. Any frames which are significantly occluded, have been omitted.

XML files are used to store information about the database to enable different evaluations to be easily performed based on which subset of the dataset fits the desired criteria. For each subject, an XML file is used to summarise the camera views and frame information which can be used to select subjects which fit the desired evaluation conditions (e.g. only subjects that exist in specific cameras or locations can be selected).

The overall dataset is also summarised in an XML file, which provides information on the camera calibration data for each subject.

These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed. This study was designed to investigate whether the presence of CCTV cameras can reduce crime by studying the cameras and crime statistics of a controlled area. The viewsheds of over 100 CCTV cameras within the city of Philadelphia, Pennsylvania were defined and grouped into 13 clusters, and camera locations were digitally mapped. Crime data from 2003-2013 was collected from areas that were visible to the selected cameras, as well as data from control and displacement areas using an incident reporting database that records the location of crime events. Demographic information was also collected from the mapped areas, such as population density, household information, and data on the specific camera(s) in the area. This study also investigated the perception of CCTV cameras, and interviewed members of the public regarding topics such as what they thought the camera could see, who was watching the camera feed, and if they were concerned about being filmed.

1. Specifications Data size : 60,000 ID

Population distribution : the race distribution is Asians, Caucasians and black people, the gender distribution is male and female, the age distribution is from children to the elderly

Collecting environment : including indoor and outdoor scenes (such as supermarket, mall and residential area, etc.)

Data diversity : different ages, different time periods, different cameras, different human body orientations and postures, different ages collecting environment

Device : surveillance cameras, the image resolution is not less than 1,9201,080

Data format : the image data format is .jpg, the annotation file format is .json

Annotation content : human body rectangular bounding boxes, 15 human body attributes

Quality Requirements : A rectangular bounding box of human body is qualified when the deviation is not more than 3 pixels, and the qualified rate of the bounding boxes shall not be lower than 97%;Annotation accuracy of attributes is over 97%

1. About Nexdata Nexdata owns off-the-shelf PB-level Large Language Model(LLM) Data, 1 million hours of Audio Data and 800TB of Annotated Imagery Data.These ready-to-go Identity Data support instant delivery, quickly improve the accuracy of AI models. For more details, please visit us at https://www.nexdata.ai/datasets/computervision?source=Datarade

Camera trap database serves as objective records of an animal’s presence at a location, and information on activity patterns (from the date and time contained in the image), behaviour, and pelage characteristics that enable individual identification (Rovero et al., 2008). Remotely-triggered cameras are used for camera trapping that automatically take images of whatever moves in front of them. It utilizes the fixed digital cameras to capture images or videos of animals in wild, with as little human interference as possible, travelling in front of the camera’s infra-red sensors (Rovero et al., 2010).

The South Korean national and local governments have been installing tens of thousands of closed-circuit television (CCTV) cameras every year in public places. As of 2023, there were about **** million cameras in operation. This represents a more than elevenfold increase since 2008. Throughout the past years, the number of cameras newly installed each year has exceeded well beyond one hundred thousand. Purpose and benefits of CCTV camerasOut of all these cameras, around half were installed for crime prevention and a further ** percent for purposes of facility safety and fire prevention. The rest were mainly intended for traffic law enforcement and various related data collection purposes. CCTV cameras are proving to be particularly beneficial in law enforcement, with the police admitting that CCTV records help solve the majority of serious crimes. Thus, the first step in any police investigation now is to obtain these records. In addition, CCTV records assist investigators searching for the cause of accidents. Should there be additional CCTV cameras?Due to these benefits, there have been calls for the installation of additional CCTV cameras to eliminate blind spots. However, there are concerns over the possibility that the government will be able to use the cameras, and the data they collect, to wield excessive power over citizens' lives, invading their privacy.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

This dataset includes both CCTV Cameras and Traffic Control Cameras within the Nottingham City Council administrative boundary.Additionally, for images captured by Traffic Control CCTV cameras, please click here to open a machine-readable JSON file which contains a catalogue of CCTV camera image locations. CCTV Camera images are published by the Traffic Control Centre in Nottingham and are updated approximately every 2 minutes. Capture times are 07:00 - 18:00 weekdays, 07:00 - 13:00 on Saturdays.

Snapshot img

Closed Circuit Television (CCTV) Market Size 2025-2029

The closed circuit television (cctv) market size is forecast to increase by USD 19.43 billion, at a CAGR of 14.2% between 2024 and 2029.

The global CCTV market is experiencing significant growth, driven by increasing government initiatives to enhance security and surveillance. These initiatives, aimed at safeguarding public spaces and critical infrastructure, are leading to increased demand for advanced CCTV systems. A key trend shaping the market is the integration of deep learning technology into CCTV systems, enabling more accurate and efficient video analysis. This development offers opportunities for companies to provide innovative solutions that can help clients manage and make sense of vast amounts of video data. However, the market also faces challenges. Cyber security risks associated with CCTV systems are becoming increasingly prominent, as these systems become more interconnected and data-driven.
Ensuring the security of video feeds and associated data is essential to maintaining the trust of clients and protecting sensitive information. Companies must prioritize robust cyber security measures and invest in research and development to stay ahead of evolving threats.

What will be the Size of the Closed Circuit Television (CCTV) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The CCTV market continues to evolve, with dynamic market activities shaping its landscape. Access control systems, integrated with user authentication, ensure secure entry and exit points in various sectors, from commercial to critical infrastructure protection. System maintenance is crucial for optimal performance, requiring regular checks on network bandwidth and traffic monitoring. Object detection technology advances, enabling more effective surveillance in retail environments and public spaces. Vandal-resistant cameras withstand harsh conditions, ensuring uninterrupted monitoring in high-risk areas. Network bandwidth requirements increase with the adoption of high-definition cameras and remote monitoring capabilities. Lens technology, including varifocal and zoom lenses, offers flexibility in capturing wide or focused views.

Alarm systems and motion detection provide instant notifications for potential threats. Security systems integration ensures seamless communication between different security components. Data storage capacity remains a significant concern, with cloud-based solutions offering scalable and cost-effective alternatives. IP cameras and live streaming enable real-time access to footage from anywhere. Facial recognition and license plate recognition add an extra layer of security, enhancing public safety and law enforcement efforts. Infrared imaging and night vision expand the capabilities of CCTV systems, enabling effective monitoring in low-light conditions. PTZ cameras offer remote control capabilities, allowing for flexible coverage of large areas. Remote troubleshooting and maintenance further enhance system reliability.

CCTV applications extend beyond traditional security, with smart cities leveraging video analytics and image sensor technology for traffic management and public safety. The ongoing development of CCTV technology continues to redefine the market landscape, offering innovative solutions for various sectors.

How is this Closed Circuit Television (CCTV) Industry segmented?

The closed circuit television (cctv) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Dome camera
  PTZ camera
  Bullet camera
  Box camera


Application

  Public
  Commercial
  Residential


Display Type

  High definition
  Standard definition
  4K and above


Technology

  IP-based CCTV
  Analog CCTV
  Hybrid systems


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW). 

By Product Insights

The dome camera segment is estimated to witness significant growth during the forecast period.

Dome cameras, a popular choice for surveillance in various sectors, come in diverse dome shapes and can be installed on walls, ceilings, or other surfaces within retail stores, hotels, banks, offices, and more. Advanced technologies like infrared night vision, artificial intelligence, and machine learning are integrated into these cameras for enhanced security. Dome cameras are available in different types, including analog, IP, wireless, network, and thermal models. Their durability and resistance to vandalism are nota

Snapshot img

Security Camera Market Size 2025-2029

The security camera market size is forecast to increase by USD 3.85 billion, at a CAGR of 12.1% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of video analytics for advanced surveillance and security applications. This technology enhances the capabilities of security cameras, enabling more effective video analyses and improving overall security systems. Another key trend shaping the market is the proliferation of IoT and smart home technologies, which are integrating security cameras into comprehensive home automation solutions. However, the market also faces challenges, including privacy concerns and the risk of data loss. As more cameras are installed in both public and private spaces, ensuring data privacy and security becomes a paramount concern.
Companies must address these challenges through robust data encryption and privacy policies to maintain customer trust and confidence. In summary, the market is poised for continued growth, fueled by advancements in video analytics and the integration of IoT technologies. However, addressing privacy concerns and mitigating the risk of data loss will be essential for market success.

What will be the Size of the Security Camera Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, with innovative technologies and applications shaping its dynamics. Object tracking, a key feature of advanced IP cameras, enhances surveillance capabilities by identifying and following moving objects. CCTV systems integrate IP cameras, video analytics, and real-time alerts, providing comprehensive security solutions. Thermal cameras offer unparalleled performance in low-light conditions, making them indispensable for outdoor surveillance. Privacy laws and cybersecurity measures are increasingly influencing the market, driving the adoption of edge recording, data encryption, and user authentication. Maintenance contracts ensure seamless system performance, while vandal-resistant housings and weatherproof enclosures extend the life of cameras.

High-dynamic-range (HDR) imaging and multi-sensor cameras deliver superior image quality, while panoramic cameras provide wide-angle coverage. Behavior analysis and anomaly detection employ machine learning and deep learning algorithms for advanced threat detection. Cloud services enable remote monitoring, video retrieval, and mobile app integration, offering flexibility and convenience. Applications span various sectors, including smart cities, where security systems are integrated with access control, intercom, and traffic management systems. Security cameras are also integrated into smart homes, offering user-friendly solutions for homeowners. The market's continuous unfolding is marked by the integration of advanced technologies, evolving regulatory frameworks, and growing demand for comprehensive security solutions.

How is this Security Camera Industry segmented?

The security camera industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Technology

  Analog
  IP based


Product Type

  HD and full-HD
  Non-HD


Application

  Commercial Surveillance
  Residential Surveillance
  Public & Government Infrastructure


End-Use Industry

  Retail
  Banking & Finance
  Transportation


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

.

By Technology Insights

The analog segment is estimated to witness significant growth during the forecast period.

The market encompasses a range of solutions, including installation services, PTZ cameras, object detection, video retrieval, remote monitoring, access control integration, bullet cameras, cloud services, night vision, smart city applications, intercom integration, deep learning, machine learning, cybersecurity measures, video archiving, data retention policies, mobile app integration, cloud storage, analog cameras, remote management, user authentication, dome cameras, behavior analysis, anomaly detection, 4k resolution, HD resolution, motion detection, smart home integration, artificial intelligence, license plate recognition, weatherproof enclosures, compliance regulations, infrared cameras, security software, tamper detection, data encryption, box cameras, surveillance cameras, automated incident response, facial recognition, fixed cameras,

2,769 People – CCTV Re-ID Data in Europe. The data includes males and females, the race distribution is Caucasian, black, Asian, and the age distribution is from children to the elderly. The data diversity includes different age groups, different time periods, different cameras, different human body orientations and postures. For annotation, the rectangular bounding boxes and 15 attributes of human body were annotated. This data can be used for re-id and other tasks.

Close-circuit television (CCTV) cameras' locations in York. For further information please visit the City of York Council website.

*Please note that the data published within this dataset is a live API link to CYC's GIS server. Any changes made to the master copy of the data will be immediately reflected in the resources of this dataset.The date shown in the "Last Updated" field of each GIS resource reflects when the data was first published.

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Access 'Ip Bullet Cctv Camera imports' with data on 6 shipments from 3 exporters to 3 importers. Search, filter and download detailed trade records.

Traffic camera locations as of June 5, 2015

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

The CSAFE Multicamera Smartphone Image Database is a digital image dataset designed for forensic science research. The dataset contains roughly 50,000 JPEG images from sixty multi-camera smartphones. This dataset is particularly useful for source camera identification experiments. By analyzing distinctive features (camera fingerprints) extracted from images, digital evidence examiners may be able to link an image to a specific camera.