Image Processing ROI Integration for Multi-Object Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image processing systems struggle with accurately setting a region of interest (ROI) due to automatic detection techniques potentially misidentifying unintended objects, leading to incorrect tracking and missed objects.
Innovation Solution
An image processing apparatus that allows users to input a locus on a touch screen to select and integrate multiple object regions, creating a more appropriate ROI by combining detected objects based on user input and integration frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automatic object detection technique is used to extract region of interest, then object detection speed is improved, but detection accuracy deteriorates due to misidentification of unintended objects
Solution Approach 1:
A locus input unit is introduced as an intermediary between automatic detection and final ROI selection. Users can input loci (points of interest) on the touch screen, and these loci serve as mediator information to guide the selection and integration of detected objects, ensuring the ROI accurately reflects user intent while maintaining automatic detection speed
Solution Approach 2:
The system provides feedback by displaying detected objects and allowing users to input loci for correction. The ROI is then regenerated based on this feedback, creating an iterative refinement process that improves accuracy while maintaining efficiency
2Measurement precision
If partial region of object is set as region of interest, then detection precision is improved, but tracking reliability deteriorates due to inability to discriminate from remaining regions
Solution Approach 1:
An integration unit combines multiple detected object regions into a unified ROI based on user-input loci. This merging process ensures the ROI is precise enough for accurate detection while being comprehensive enough to maintain tracking reliability by including all relevant object portions
3Measurement precision
If user operation is added to correct region of interest, then region of interest accuracy is improved, but device complexity increases
Solution Approach 1:
Users directly input loci on the touch screen interface to specify their desired ROI. The system then automatically processes these loci through the selection and integration units, allowing users to self-correct the ROI without requiring complex manual adjustments or additional hardware controls
Data Source
AI summary
An image processing apparatus comprises: an image input unit configured to input an image; a detection unit configured to detect an object from the image; an accepting unit configured to accept an input of a locus to the image; a selection unit configured to select, based on a locus region decided by the locus, at least two objects included in a plurality of objects detected by the detection unit; and an integration unit configured to generate an integration region that integrates at least two regions in the image corresponding to the at least two objects selected by the selection unit and set the integration region as a region of interest in the image.