Motion Detection System Using Dual Buffer Segmentation
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Solution Overview
Problem
Conventional motion detection systems face challenges with high computational complexity, leading to substantial resource consumption and latency, making them unsuitable for real-time applications and hardware design, especially in low-power environments where power efficiency is crucial.
Innovation Solution
A motion detection system that employs a buffer-based approach with two buffers for background and foreground images, using pixel-level analysis to determine still and moving pixels, facilitating pipelining and reducing latency through down-sampling and efficient buffer management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional motion detection algorithms are used, then motion detection capability is achieved, but computational complexity increases and latency is induced
Solution Approach 1:
The patent segments the image processing into distinct stages: down-sampling input images to reduced resolution, then processing through multiple motion detection algorithms (first and second algorithms) on different buffer pairs. This segmentation reduces the computational burden on each individual algorithm while maintaining overall detection accuracy, directly addressing the contradiction between detection capability and computational complexity.
Solution Approach 2:
The patent applies partial action by using multiple motion detection algorithms with different thresholds and buffer configurations. The first motion detection algorithm processes buffers with a first threshold, while the second algorithm uses a second threshold, allowing the system to detect motion at multiple levels of sensitivity without requiring a single complex high-threshold algorithm.
2Reliability
If conventional motion detection algorithms are used, then motion detection capability is achieved, but latency increases
Solution Approach 1:
The patent performs down-sampling of input images before motion detection processing, creating reduced-resolution images in advance. This preliminary action reduces the amount of data that subsequent motion detection algorithms must process, thereby reducing latency while maintaining detection capability. The down-sampled images are prepared beforehand, allowing faster processing in the motion detection stage.
3Reliability
If complex architecture is used for motion detection, then detection accuracy is improved, but hardware design suitability decreases
Solution Approach 1:
The patent divides the motion detection system into modular components: down-sampling units, multiple buffer pairs, and separate motion detection algorithm units. Each component has a specific function and can be independently implemented in hardware. This modular segmentation makes the system easier to manufacture and deploy in hardware while maintaining detection accuracy through the coordinated operation of multiple simpler units.
4Measurement precision
If high resolution processing is used, then image quality is maintained, but buffer usage increases
Solution Approach 1:
The patent segments the image data into down-sampled versions and processes these segmented representations in multiple buffer pairs. Instead of maintaining full-resolution images in memory, the system creates smaller down-sampled image segments that fit into smaller buffers, reducing overall buffer usage while maintaining sufficient image quality for motion detection through the use of multiple algorithmic approaches.
Data Source
AI summary
A motion detection method includes providing a buffer including a first buffer associated with a background image and a second buffer associated with a foreground image; checking first similarity between the gray level of an input pixel and the first gray level of the first buffer; determining the input pixel as a still pixel if the first similarity is true; checking second similarity between the gray level and the second gray level of the second buffer; determining the input pixel as a moving pixel if the second similarity is false; determining the input pixel as the moving pixel if the second count value is less than the first count value; and determining the input pixel as the still pixel and swapping the first buffer with the second buffer, if the second count value is not less than the first count value.