Intelligent Analysis Technology Application Advantages and Bottleneck Analysis
Intelligent video analysis involves using computer-based image processing technology to interpret the content displayed on video screens. This technology separates the background from the subject within a scene and analyzes and tracks the entities appearing in it. By setting different analytical rules in the camera's field of view, the system can trigger preset actions whenever the subject violates those rules, enabling an active alarm mechanism.
From a product perspective, intelligent analysis systems come in two primary forms. One employs intelligent algorithms combined with DSPs, typically found in front-end intelligent analysis cameras and video servers. These systems place the software and hardware with intelligent analysis functions at the video capture stage. In conventional surveillance systems, video data takes up significant storage space and bandwidth. Solving these issues is a major challenge. Much of the stored and transmitted video is unnecessary, wasting both storage capacity and bandwidth. The goal of intelligent analysis is to reduce the space needed for video storage and the bandwidth demands for transmission, allowing for lower-quality streaming of less critical footage. This enhances the practical value of the surveillance system. Processing happens at the front end, reducing backend service loads, enabling numerous intelligent analysis cameras to be deployed within a single system.
The second type operates via backend PC servers paired with intelligent analysis software, like Aimetis and iOmniscient. This method leverages the backend server’s processing power, which often surpasses that of front-end intelligent cameras. However, due to the significant hardware resources consumed by the algorithms, simultaneous multi-analysis tasks can overwhelm the system’s processing capability. Despite this limitation, the backend server approach, with its robust processing abilities, is typically used in high-importance intelligent analysis scenarios.
**Benefits of Smart Analytics Applications**
Intelligent analysis has two main application directions. One is license plate recognition and facial recognition technology, primarily used in electronic toll collection, mechanical engineering, and customs. The other focuses on behavioral analysis, including perimeter protection, population statistics, automatic tracking,逆行 detection, and no-parking zones, which are applicable to perimeters, shopping malls, traffic management, scenic area visitor counts, and road violations.
1. Dual-Track Automatic Tracking: Combining intelligent analysis cameras with standard PTZ cameras can track subjects during urban emergencies.
2. Flow Statistics: Counting people entering and exiting specific areas helps supermarkets analyze customer flow, aiding business strategy formulation. It also provides traffic data for attractions and subway stations.
3. Crossing Alert Zones: Setting up virtual fences around restricted areas triggers alarms when unauthorized individuals cross them. This is useful at pedestrian crossings, plant walls, schools, and detention centers.
4. Loss Analysis: Marking an area as an alert zone ensures an immediate alarm if an important item is moved. Ideal for museums, galleries, auction houses, and jewelry stores.
5. Direction Analysis: Identifying movement patterns helps assess legality of movement, flagging reverse behaviors instantly. Useful for one-way roads and key entry points.
6. Intelligent Tracking: Locking onto a suspect and tracking their movements can assist in identifying suspects and analyzing crime scenes post-incident.
The intelligent video analysis system reduces the burden on security personnel by automating tedious monitoring tasks and allows quick searches through vast video archives for specific footage. Research shows that after 10 minutes of continuous video watching, 90% of information is overlooked, making traditional monitoring inefficient. However, intelligent video analysis transforms passive monitoring into proactive defense, offering cost-effective security solutions across industries.
**Challenges in Intelligent Analysis Technology**
Is video analytics a universal solution? What are its limitations? In real-world settings, variations in lighting, target motion complexity, occlusions, target-background color similarities, and chaotic backgrounds complicate target detection and tracking algorithms. Let’s examine some specific factors impacting smart analytics:
Background Complexity: Changes in lighting due to target or background color shifts may cause false detections and tracking errors. Different color spaces can mitigate lighting impacts but cannot eliminate them entirely; moving objects and background swaps, vehicle starts/stops, and similar target-background colors hinder detection and tracking. Shadow differences often misidentify moving targets, complicating segmentation and feature extraction.
Trade-offs in Target Features: Sequential images hold abundant tracking-relevant features like motion, color, edges, and textures. Yet, these features constantly change, making it challenging to select optimal ones ensuring effective tracking.
Occlusion Issues: Occlusion is a critical issue in tracking. Partial or complete blockage of moving targets, or mutual occlusion among multiple targets, results in lost target information affecting tracking stability. Correctly handling feature-target correspondences reduces occlusion ambiguities. Statistical prediction of target locations and scales works for mild occlusions but struggles with severe cases.
Real-Time & Robustness: Handling vast image information requires lightweight algorithms for real-time tracking. Algorithm robustness ensures adaptability to complex backgrounds, lighting changes, and occlusions, though at the cost of computational complexity.
To address these challenges, we can improve system effectiveness and practicality in several ways:
1. Optimize algorithms and tailor strategies to specific scenarios for better algorithm accuracy.
2. Strategically position cameras to enhance analysis precision, relying heavily on the angle’s rationality.
3. Introduce supplementary equipment like fill lights or infrared sources for application under diverse conditions.
The video intelligence analysis system represents the future of video surveillance, becoming a core tool for extracting valuable insights from large datasets. Its integration with high-definition and intelligent capabilities, along with the convergence of cameras and intelligent analysis, will expand its role and influence. Transforming traditional human security into technical defenses, it promises to revolutionize surveillance systems.
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