Video Processing Unit Thermal Signature Newcomer Detection
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Solution Overview
Problem
Current video processing systems face challenges in distinguishing newcomers from long-term occupants in surveillance environments due to computational limitations and uniform bitrate encoding, making it difficult to prioritize and efficiently analyze potential intruders in real-time.
Innovation Solution
A method that captures thermal images to calculate thermal signatures, differentiating newcomers from long-term occupants by their climate deviations, and prioritizes these individuals for enhanced video processing, including higher computational resources and bitrate allocation, to facilitate early detection and identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video analytics tools are used to identify and match all people in the video to a record of identities, then detection of newcomers and intruders is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent applies local quality by differentiating processing levels for different regions of interest in the video. Newcomers and suspected intruders (who have been in the environment for less than a threshold time) receive higher priority processing with more computational resources, while long-term occupants receive standard processing. This resolves the contradiction by concentrating computational complexity only where it is most needed for detection accuracy.
Solution Approach 2:
The patent segments the video processing task by dividing it into multiple processing stages and priority levels. Video frames are processed to identify individuals, determine their tenure in the environment, and then routed to appropriate processing queues. This segmentation allows the system to handle the overall detection task with reduced computational complexity at each stage rather than applying full complexity uniformly to all frames.
2Ease of manufacture
If uniform compression level is applied to all people in the video, then encoding simplicity is maintained, but detection quality of newcomers deteriorates
Solution Approach 1:
The patent implements local quality in the encoding stage by applying different compression levels to different individuals based on their detection priority. Suspected newcomers and intruders are encoded with higher quality (lower compression) to preserve detection features, while long-term occupants are encoded with standard compression. This resolves the contradiction by maintaining encoding simplicity through automated differential compression rather than uniform encoding.
3Ease of operation
If computational resources are allocated uniformly to all individuals in the video, then resource allocation simplicity is maintained, but detection efficiency of newcomers deteriorates
Solution Approach 1:
The patent applies local quality to resource allocation by dynamically assigning different computational resource levels to different individuals based on their temporal presence in the environment. Suspected newcomers receive prioritized processing with more computational resources allocated to their analysis, while long-term occupants receive standard resource allocation. This resolves the contradiction by maintaining simple automated resource management rules while achieving high detection efficiency for critical targets.
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 effectively focuses computational efforts and bitrate on suspected newcomers, improving their detection and identification by prioritizing their analysis and encoding, thereby enhancing security in surveillance applications.
Implementation Method 1
capturing, a thermal image of a human object in the first environment
Data Source
AI summary
A method and a controller for controlling a video processing unit to facilitate detection of newcomers in a first environment. The method comprises: capturing a thermal image of a human object in the first environment, the first environment being associated with a first climate; calculating, based on the thermal image, a thermal signature of a portion of the human object; determining that the human object has entered the first environment from a second environment when the thermal signature of the portion of the human object deviates from a predetermined thermal signature associated with the first environment, wherein the second environment is associated with a second, different, climate; and controlling the video processing unit to prioritize the human object over other human objects when processing video frames depicting the human object together with the other human objects.