AI Object Recognition with Coarse-to-Fine Classification
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Solution Overview
Problem
Current image recognition methods require users to perform multiple operations to activate and manage image recognition functions, are inefficient for recognizing multiple target objects, and often require manual selection, leading to complexity and low efficiency.
Innovation Solution
A method and apparatus that automatically recognize target objects from images displayed by an imaging camera, displaying coarse classification results initially, followed by refined classification results, with filtering and animation effects to enhance user experience, and allowing detailed information to be accessed upon user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually activate image recognition through multiple operations (launching plug-in, clicking button, uploading image), then the recognition function can be activated, but the operation complexity increases and efficiency decreases
Solution Approach 1:
The system automatically activates image recognition and processes images without requiring user intervention. The electronic device autonomously captures images, performs recognition, and displays results, eliminating the need for users to manually launch plug-ins, click buttons, or upload images.
Solution Approach 2:
The system performs preliminary actions by automatically capturing images and initiating recognition processes before user requests. The image recognition function is pre-configured and automatically executes when imaging conditions are met, eliminating the need for manual activation steps.
2Measurement precision
If the system provides only coarse classification recognition results, then the processing speed is faster, but the recognition precision is insufficient
Solution Approach 1:
The recognition process is segmented into multiple stages: first providing coarse classification results for quick feedback, then progressively refining to finer classification levels. This multi-stage segmentation allows the system to balance speed and precision by delivering results at different granularity levels.
Solution Approach 2:
The system performs preliminary coarse classification recognition first to provide immediate feedback, then subsequently performs detailed fine-grained recognition. This preliminary action approach allows users to quickly understand general categories while the system continues to refine results for higher precision.
3Loss of information
If the system displays detailed information for all recognized objects, then the information completeness increases, but the display complexity and user cognitive load increases
Solution Approach 1:
Different levels of detail are provided for different objects based on their relevance and user interest. The system displays coarse classification results for all objects, then provides detailed fine-grained information selectively for objects that require closer examination or user interaction.
Solution Approach 2:
Information display is segmented into hierarchical levels: basic coarse classification information is displayed for all recognized objects, while detailed attributes and characteristics are displayed only for objects selected for further examination, reducing overall display complexity.
Data Source
AI summary
The present disclosure provides a method and an apparatus for recognizing a target object, an electronic device and a storage medium, relating to a field of artificial intelligence. The method includes the following. A target object is recognized from a first image displayed by an imaging camera. A first recognition result of the target object is obtained. The first recognition result of the target object is displayed in the first image. A second recognition result of the target object is obtained and displayed to replace the first recognition result.