Cargo Space Motion Detection Using Variable Image Queue Comparison
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Solution Overview
Problem
Existing methods for detecting object movement in vehicle cargo spaces are not capable of real-time detection and require complex training procedures, leading to inefficiencies and increased hardware costs.
Innovation Solution
A method utilizing successive image acquisition with a variable FIFO queue, comparing recent and older images to detect object movement, allowing real-time detection of both fast and slow movements without prior training, using commercially available image capture devices and processors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex training procedures are used for object detection, then detection accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The patent segments the detection task into two distinct comparison operations: comparing the most recent image with the immediately preceding image to detect fast movements, and comparing the most recent image with the oldest image in the queue to detect slow movements. This segmentation allows the system to detect different movement types using simple comparison operations rather than complex training-based approaches.
Solution Approach 2:
The patent performs two comparison operations within a single processing cycle, which could be considered excessive action. By comparing the most recent image with both the immediately preceding image and the oldest image simultaneously, the system ensures comprehensive detection of both fast and slow movements without requiring complex algorithms.
2Measurement precision
If complex training procedures are used for object detection, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The detection task is segmented into two parallel comparison operations that can be executed efficiently within a single processing cycle. By dividing the detection into fast movement detection (recent vs. immediately preceding image) and slow movement detection (recent vs. oldest image), the system achieves comprehensive detection without the time cost of complex training procedures.
Solution Approach 2:
The system maintains a queue of previously captured images in memory, performing preliminary action by storing these images for future comparison. This allows the system to immediately compare the most recent image with both the immediately preceding and oldest images without requiring additional image capture time, enabling real-time detection.
3Productivity
If high-performance specialized hardware is used for detection, then real-time detection capability is improved, but hardware costs increase
Solution Approach 1:
The patent makes the image capture device and processor serve multiple functions: capturing images for monitoring, storing images in the queue, performing comparisons for movement detection, and enabling both fast and slow movement detection within a single processing cycle. This multi-functionality eliminates the need for specialized high-performance hardware while achieving real-time detection capability.
Solution Approach 2:
The system uses commercially available image capture devices and processors that are already capable of the required operations. The standard hardware performs the detection functions without requiring specialized or high-performance components, reducing hardware costs while maintaining real-time detection capability through efficient algorithm design.
4Duration of action of stationary object
If image capture devices are permanently attached and mechanically independent, then system lifespan is improved, but detection of all object types requires prior training
Solution Approach 1:
The detection approach is segmented into movement-based detection rather than object-type-based detection. By comparing images to identify pixel differences and calculating movement indicators, the system detects any object that causes visible movement without requiring prior knowledge or training about specific object types, maintaining both durability and versatility.
Data Source
AI summary
The invention relates to a method for detecting the movement of at least one object in the cargo space of a vehicle, wherein at least two images (2.1; 2.2; 2.3; 2.4; 2.5; 2.6; 2.7; 2.8) are taken successively by means of at least one image acquisition device, and wherein images (2.1; 2.2; 2.3; 2.4; 2.5; 2.6; 2.7; 2.8) taken at different times are compared. According to the invention, at least the following method steps are carried out: • Feeding the successively taken images (2.1; 2.2; 2.3; 2.4; 2.5; 2.6; 2.7; 2.8) into a queue (1), wherein the length of the queue (1) is variable; • Comparing the most recent image (2.2) of the queue (1) with both the immediately preceding image (2.3) of the queue (1) to determine a first movement indicator value (15) and with the oldest image (2.7) the queue (1) to determine a second movement indicator value (16); • detection of movement if the first movement indicator value (15) is greater than "0", or if the first movement indicator value (15) is equal to "0" and the second movement indicator value (16) is greater than "0".