Image Region Identification Using Neural Network Feature Comparison
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Solution Overview
Problem
Current technologies lack an efficient method to identify and retrieve images that depict specific items, such as clothing or other personal items, from a collection of images, making it difficult for users to recall past outfits or find matching items.
Innovation Solution
The use of trained convolutional neural networks and Siamese networks to compare features of items with regions-of-interest (ROIs) in images, determining similarity and outputting images that match the query item, with adjustable ROI sizes based on item size and image depth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional image search methods are used, then users can search for images, but they cannot efficiently identify and retrieve images of specific items from a collection
Solution Approach 1:
The patent divides the image into multiple regions of interest (ROIs) corresponding to different body parts (head, torso, legs, etc.), allowing the system to selectively search for items in specific regions rather than analyzing the entire image, thereby improving identification efficiency and accuracy
Solution Approach 2:
The patent introduces a region-of-interest (ROI) as an intermediary between the user's item query and the image data, enabling the system to map user-friendly item descriptions to specific image regions and retrieve relevant images efficiently
2Reliability
If the system analyzes the entire image for item identification, then it can find all possible matches, but it increases processing time and computational complexity
Solution Approach 1:
The patent segments the image into multiple ROIs representing different body parts, allowing the system to process only the relevant regions where items are likely to appear, significantly reducing processing time while maintaining detection accuracy through targeted analysis
Solution Approach 2:
The patent applies partial action by analyzing only the necessary portions of the image (ROIs) rather than the entire image, optimizing the balance between processing thoroughness and computational efficiency
Data Source
AI summary
The techniques described herein may identify images that likely depict one or more items by comparing features of the items to features of different regions-of-interest (ROIs) of the images. When a user requests to identify images that depict a particular item, the techniques may determine a region-of-interest (ROI) size based on the size of the requested item. The techniques may then search multiple images using the ROI size.