Re-ID Dataset Empowers Security: Ushering in a New Era of Intelligent Protection

With the rapid development of science and technology, security sector has become a crucial point for AI to demonstrate its capabilities. Data shows that the global AI security market will exceed $45 billion in 2025, with a compound annual growth rate of 28.6%. From city streets to key locations, from facial recognition to cross-camera tracking, AI security has become a digital "guardian" of public safety.

 

A New Paradigm for AI-Powered Security Applications in Multiple Scenarios

From early simple video surveillance to today's intelligent, automated security systems, the application of AI technology has profoundly transformed numerous areas, including urban safety, traffic management, and public order maintenance. The following will detail the extensive applications and significant value of AI in security, focusing on applications such as facial and body recognition, ReID (cross-camera tracking), vehicle identification, and identification for refined urban governance scenarios.

 

Facial and body recognition: The "Cornerstone of Identity Authentication" for Security

In AI-powered security systems, facial and body recognition is the most fundamental and widely used technology. By extracting biometric features (such as facial contours and texture) and combining them with deep learning algorithms, facial recognition systems can quickly and accurately identify individuals. This technology is extremely useful in scenarios such as access control, attendance management, and security checks, improving access efficiency and enhancing security. Human body recognition focuses more on analyzing individual behavior. By extracting features such as posture and movement trajectory, the system can detect abnormal behavior in real time and immediately issue an alert, notifying security personnel for timely intervention. This effectively prevents potential security risks and ensures safety and order in public areas.

 

ReID Technology: A Powerful Tool for Continuous Tracking Across Cameras

ReID technology offers unique advantages in the field of AI security, particularly in tracking individuals across cameras and scenarios. It can accurately identify and retrieve pedestrians based on features such as clothing, posture, and hairstyle across cameras and scenarios, significantly improving the accuracy and efficiency of pedestrian identification. For example, in criminal investigations, ReID technology can analyze and match the characteristics of the entire human body to quickly collect video clips of the individual within massive surveillance video libraries. This allows the suspect's trajectory across different cameras to be linked, providing key clues for solving cases and significantly improving efficiency. Furthermore, ReID technology can also be applied to intelligent person-finding systems, helping to quickly locate lost individuals in large public spaces and saving valuable time in the search process.

 

Vehicle Identification: The Core Driving Force of Intelligent Traffic Management

Vehicle identification technology is a core application of AI security in the transportation sector. AI systems recognize features such as license plates, models, colors, and logos to accurately identify and manage vehicles. At intersections, vehicle identification systems automatically record vehicle traffic information, providing strong evidence for investigating and enforcing traffic violations. This not only improves the efficiency and accuracy of traffic enforcement, but also effectively curbs traffic violations and promotes civilized and safe urban transportation. Furthermore, vehicle flow analysis can optimize traffic signal scheduling, alleviate urban congestion, and enhance public safety.

 

Scene Identification: Comprehensively Improving Urban Refinement and Security Management

With the advancement of AI technology, security applications have expanded from individual identification to scene-level analysis, providing city managers with new perspectives and tools. By monitoring and analyzing various urban scenes in real time, AI systems can intelligently manage the urban environment and public facilities. For example, in urban environmental monitoring, AI scene recognition can also be combined with IoT devices to realize functions such as garbage accumulation monitoring, road occupation business warning, and fire passage blockage detection, so that relevant management departments can carry out timely cleaning and repair, thereby keeping the city clean and beautiful; in public safety management, AI scene recognition technology can monitor scenes such as open-air barbecues, flames, and fog. Once a problem is discovered, the system can promptly notify maintenance personnel to conduct supervision, effectively control urban chaos, and ensure public safety.

 

AI Security Systems: Data is the Core Driving Force

The efficient operation of AI security systems relies on high-quality data. Extracting valuable data from massive amounts of surveillance video and images, and analyzing and processing it, is key to AI security systems achieving accurate identification and early warning.

 

In terms of data quality and quantity, the dual driving forces of data quality and scale in the AI security field are the core guarantees for model accuracy. Data authenticity and annotation accuracy must be strictly guaranteed. For example, facial recognition requires accurate annotation of key facial features to avoid recognition failures due to incorrect annotations. Data must also cover comprehensive security elements such as person identity, vehicle characteristics, and behavioral trajectory, forming a multi-dimensional information closed loop. All data sources must have standardized formats, timestamps, and content standards to ensure consistent analysis across systems. Data scale is also crucial. Large, diverse datasets are the cornerstone of model generalization. Only by synergizing "quality" and "quantity" can a reliable AI security defense be built.

 

In terms of data diversity, data should encompass multiple types, such as images, videos, audio, and text, and should be collected from different scenarios, time periods, and climate conditions. This can improve the adaptability and robustness of AI models in various real-world scenarios.

 

Nexdata: A Data Treasure House for the Security Industry

 

As a professional data services provider, Nexdata has accumulated a rich data set in the security field, providing a solid data foundation for the development of AI security technology. Nexdata's security data set covers multiple dimensions, meeting the diverse needs of different clients:

 

・Overhead Surveillance Video Dataset for Human Tracking - 11,352 Videos: This dataset contains 11,352 overhead surveillance videos recorded in diverse indoor and outdoor scenarios across various time periods. Captured from top-down views, the data is suitable for tasks such as human detection, pedestrian tracking, people counting, and human body attribute analysis. It is ideal for developing and benchmarking computer vision models in surveillance and security applications. All data are legally sourced and fully compliant with GDPR, CCPA, and PIPL.

 

・Multi-view Person Tracking Dataset – 4,001 Subjects for Re-ID and Computer Vision Tasks: This data covers both indoor and outdoor scenarios. The data includes both men and women, ranging in age from children to the elderly. The data is diverse, encompassing different age groups, time periods, camera angles, body orientations and postures, and seasonal clothing. All personal data has been authorized by the individuals or their guardians. The data includes body rectangles and 15 body attribute information, achieving an accuracy rate exceeding 97%.

 

・212 People – 48,000 Images of Multi-person and Multi-view Tracking Data: The data includes males and females, and the age distribution is from children to the elderly. The data diversity includes different age groups, different shooting angles, different human body orientations and postures. For annotation, we adpoted rectangular bounding boxes annotations on human body. This dataset can be used for multiple object tracking and other tasks.

 

In the future, as all kinds of data are collected and annotated, how will AI technology change our lives gradually? The future of AI data is full of potential, let's explore its infinity together. If you have data requirements, please contact Nexdata.ai at [email protected].