Object Detection Device Using Predictive Partial Area Segmentation
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Solution Overview
Problem
Existing object detection systems on edge devices suffer from accuracy degradation when a part of an image is used as a detection target, particularly due to changes in aspect ratios between past and current images.
Innovation Solution
An object detection device that predicts an object presence area in a current image based on past image detection results, generates object presence partial areas with associated information, detects partial objects within these areas, and restores detection results by placing detected objects back into the predicted presence area, thereby reducing computational load and maintaining accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If object detection is performed on a partial area of the image to reduce computational load, then processing speed is improved, but detection accuracy deteriorates due to aspect ratio changes between past and current images
Solution Approach 1:
The patent divides the object presence area into multiple partial areas and performs object detection on each partial area separately. This segmentation allows the system to process only relevant portions of the image while maintaining accuracy through subsequent synthesis of results from all partial areas.
Solution Approach 2:
The patent introduces an intermediary process that uses past image detection results to predict the object presence area in the current image, then refines this prediction by performing detection on partial areas. This intermediary prediction step bridges the gap between computational efficiency and detection accuracy.
2Use of energy by moving object
If object detection is performed only on partial areas to reduce computational load, then energy consumption is reduced, but detection reliability deteriorates
Solution Approach 1:
The patent segments the object presence area into multiple partial areas and performs detection on each. By processing multiple segments in parallel and synthesizing their results, the system maintains reliable detection while reducing overall energy consumption compared to processing the entire image.
Solution Approach 2:
The patent performs object detection on partial areas rather than the entire image. This partial action approach processes only the necessary portions of the image, reducing energy consumption while maintaining sufficient detection reliability through comprehensive coverage of the predicted object presence area.
3Measurement precision
If the entire image is used for object detection to maintain accuracy, then detection accuracy is preserved, but processing time increases
Solution Approach 1:
The patent segments the image into the object presence area and other areas, then further divides the object presence area into partial areas for detection. This segmentation allows the system to focus computational resources only on relevant regions, reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent performs preliminary prediction of the object presence area using past image detection results before performing actual object detection. This preliminary action identifies the relevant regions in advance, allowing the subsequent detection process to focus only on those areas and reduce overall processing time.
Data Source
AI summary
An object detection device includes a prediction unit which predicts an object presence area, which is an area where an object is present in a current image, based on results of object detection in a past image, a generation unit which generates an object presence partial area that includes a partial area of the predicted object presence area together with partial information, which is information indicating a position of the partial area in the predicted object presence area and a size of the partial area, a detection unit which detects partial objects that are part of the object by performing object detection on the generated object presence partial area, and a restoration unit which restores results of object detection in the current image by placing the partial objects detected using the generated partial information in the predicted object presence area.