Image Question Answering with Automatic Object Region Extraction
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Solution Overview
Problem
Existing techniques for generating answers to questions about objects in images using vision language models require manual drawing of circles around objects, which is time-consuming.
Innovation Solution
An auto reply device that preprocesses images to extract a predetermined region based on the question, using object recognition and posture analysis to determine the relevant area, and inputs the preprocessed image and question into a trained generation model to generate an answer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual drawing of red circles around objects is used to draw VLM attention, then the model can focus on the object of interest, but the process becomes very time-consuming
Solution Approach 1:
The system performs preliminary object recognition and region extraction automatically before the VLM processing stage. By pre-identifying objects and their bounding boxes using object recognition models, the system eliminates the need for manual red circle drawing, thus reducing time consumption while maintaining accurate object focus in the subsequent VLM generation process
Solution Approach 2:
The manual mechanical process of drawing red circles is replaced by an automated computational system. Object recognition algorithms automatically generate bounding boxes around detected objects, substituting the manual drawing action with an automated image processing mechanism that achieves the same attention-directing function without human intervention
2Ease of operation
If the entire image is inputted into the VLM, then no manual region selection is needed, but the processing time and computational load increase
Solution Approach 1:
The system segments the input image by automatically extracting only the relevant object regions identified through object recognition. Instead of processing the entire image, the VLM receives pre-segmented regions containing only the objects of interest, which reduces computational load and processing time while maintaining ease of operation through automated region extraction
Solution Approach 2:
The system applies different processing quality levels to different regions of the image. Objects identified as relevant receive focused processing with extracted bounding boxes, while irrelevant regions are excluded. This local quality approach optimizes processing efficiency by concentrating computational resources on important areas rather than uniformly processing the entire image
Data Source
AI summary
An auto reply device includes a processor configured to pre-process an image to extract a predetermined region in the image, depending on a question, and generate an answer to the question by inputting a pre-processed image and the question into a generation model that has been trained to generate the answer.