IR Camera Scene Analysis for False Alert Reduction
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Solution Overview
Problem
Current video surveillance systems face challenges in efficiently utilizing infrared emitters to identify scene properties and reduce false security alerts, often resulting in unnecessary data collection and increased human review burden due to inadequate motion detection.
Innovation Solution
The implementation of a process that generates lookup tables to estimate spatial depth in a visual scene using a 2-dimensional array of image sensors and infrared illuminators, allowing for the creation of depth maps and classification of objects, such as windows, floors, and ceilings, while also reducing false positive alerts by excluding known regions from motion detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If infrared emitters are used to illuminate the scene for better visibility and depth estimation, then image quality and scene analysis accuracy are improved, but energy consumption and device complexity increase
Solution Approach 1:
The system activates infrared emitters periodically rather than continuously, using them only when depth information is needed for scene analysis. The emitters are turned on during specific time intervals to capture depth data, then turned off to conserve energy, maintaining measurement precision while reducing overall energy consumption.
Solution Approach 2:
The infrared emitter array is divided into multiple independently controllable segments or groups. Instead of activating all emitters simultaneously, the system selectively activates specific segments based on the scene requirements, reducing energy consumption while maintaining sufficient illumination and depth estimation accuracy for the area of interest.
2Reliability
If all regions in the scene are monitored for motion detection, then security coverage is improved, but false positive alerts increase due to irrelevant motion detection
Solution Approach 1:
The system extracts and identifies specific regions in the scene that are prone to generating false positive alerts, such as areas with frequent environmental motion (leaves, shadows, pets). These regions are then excluded from motion detection monitoring, allowing the system to maintain comprehensive security coverage in important areas while filtering out harmful false alerts from identified problematic zones.
Solution Approach 2:
The system uses depth information and scene analysis feedback to dynamically adjust motion detection sensitivity in different regions. Areas identified as generating frequent false positives have their detection thresholds adjusted or are excluded from monitoring, while maintaining high sensitivity in critical security zones, thereby reducing false alerts without compromising overall security coverage.
3Measurement precision
If depth maps and scene analysis are performed continuously, then object classification accuracy is improved, but processing time and computational load increase
Solution Approach 1:
The system performs preliminary scene analysis and depth mapping only when needed to establish baseline scene understanding, rather than continuously. Once the scene structure is mapped and regions are identified (such as windows, floors, ceilings, and false-positive-prone areas), this information is cached and reused for subsequent motion detection operations, maintaining classification accuracy while significantly reducing continuous processing time and computational load.
4Measurement precision
If infrared illuminators are activated to capture scene depth information, then spatial depth estimation accuracy is improved, but heat generation and energy consumption increase
Solution Approach 1:
The infrared illuminators are activated in periodic pulses rather than continuously, allowing the system to capture necessary depth information intermittently. This periodic activation maintains spatial depth estimation accuracy for scene analysis while providing cooling intervals that reduce heat generation and overall energy consumption from the infrared emitters.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy and efficiency of video surveillance by providing detailed scene analysis, reducing false alerts, and improving user satisfaction by automating the identification of relevant motion events and zone adjustments based on camera movement.
Implementation Method 1
the camera system includes a 2-dimensional array of image sensors (e.g., photodiodes) and a plurality of IR illuminators
Implementation Method 2
a 2-dimensional array of image sensors (e.g., photodiodes) and a plurality of IR illuminators in fixed locations relative to the array of image sensors
Data Source
AI summary
A camera system includes non-volatile memory, a lens, an image sensor to capture images of a scene within view of the lens, an IR illuminator, and a processing system. The processing system transitions the camera system from day mode to night mode when the scene is dark, and in the night mode, two operations are performed. The first operation uses the IR illuminator, the image sensor, and the memory to capture a first IR image or video of the scene and store the first IR image or video in the non-volatile memory. The second operation uses the IR illuminator, the image sensor, and the memory to identify a specular surface in the scene. This includes capturing a second IR image or video, identifying a first region of low intensity pixels, and storing, in the non-volatile memory, position parameters of the first region and designating the first region as specular.