Heterogeneous Platform Target Detection with Density-Based Processor Dispatch
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Solution Overview
Problem
Existing target detection methods on heterogeneous platforms face reduced processor performance when detecting multiple targets due to high computational demands.
Innovation Solution
A target detection method utilizing a heterogeneous platform with a first processor and a second processor, where the first processor preprocesses images and determines target thresholds, sending frames to the second processor for feature extraction when targets exceed a threshold, and independently processing frames when targets are below the threshold, optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a single processor is used for detecting multiple targets, then the detection coverage is improved, but the processor performance is reduced
Solution Approach 1:
The patent divides the target detection task into two segments: a first processor handles preprocessing and frames with fewer targets, while a second processor handles frames with more targets. This segmentation allows each processor to operate within optimal performance ranges, preventing the single processor from being overloaded while maintaining comprehensive detection coverage.
Solution Approach 2:
The patent implements dynamic task distribution where the system adapts the processing workload based on the number of targets detected in each frame. When the number of targets exceeds a threshold, the system dynamically shifts to using the second processor. This dynamic adjustment ensures that processor performance is maintained while accommodating varying detection requirements.
2Productivity
If a heterogeneous platform with multiple processors is used, then the detection efficiency is improved, but the device complexity is increased
Solution Approach 1:
The first processor serves multiple functions: it performs preprocessing on images, detects the number of targets, and determines whether to invoke the second processor. This multi-functionality reduces the need for separate dedicated components, thereby managing system complexity while maintaining high detection efficiency through the heterogeneous platform.
Solution Approach 2:
The system uses feedback from the first processor's target count detection to dynamically control the second processor's activation. This feedback mechanism ensures that the complex heterogeneous platform operates only when necessary, optimizing the balance between detection efficiency and system complexity by avoiding unnecessary computational overhead.
Data Source
AI summary
Disclosed are a target detection method based on a heterogeneous platform, a terminal device and a storage medium. A specific implementation solution is as follows: a first processor receives a video stream image, and is able to first determine a number of targets in an Nth-frame image when performing target detection on an (N+K)th-frame image in the video stream image; when the number of targets in the Nth-frame image is greater than or equal to a target threshold, the first processor is able to send the pre-processed (N+K)th-frame image to a second processor, so that the second processor cooperates with the first processor to complete target detection on the (N+K)th-frame image; and when the number of targets in the Nth-frame image is less than the target threshold, the first processor is able to perform target detection on the (N+K)th-frame image individually.