Object Recognition Device Using Adaptive Feature Value Sets
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Solution Overview
Problem
Existing object recognition systems face challenges in accurately identifying objects in varying environmental conditions, such as daytime vs. nighttime, due to differences in lighting and environmental factors, which can lead to difficulties in selecting appropriate feature value sets for accurate recognition.
Innovation Solution
A device and method that utilize a combination of multiple feature value sets based on environmental information, such as time and location, to determine weights and use frequencies for enhanced object recognition, allowing for more accurate identification by applying different feature value sets depending on the context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single feature value set is used for object recognition, then the device complexity is low, but the recognition accuracy deteriorates in varying environmental conditions
Solution Approach 1:
The patent implements dynamic selection of feature value sets based on environmental conditions. The processor determines current environmental parameters (time, location, lighting) and adaptively switches between different feature value sets (first feature value set for daytime, second feature value set for nighttime) to optimize recognition accuracy for varying conditions.
Solution Approach 2:
The patent changes the parameters of feature value sets according to environmental conditions. Different feature value sets are prepared with parameters optimized for specific environments (e.g., lighting conditions, time of day), and the system selects the appropriate set by changing which parameter set is actively used based on detected environmental parameters.
2Measurement precision
If multiple feature value sets are prepared for different environments, then the recognition accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the feature value sets into distinct groups based on environmental conditions. Instead of using one comprehensive feature set, the system divides recognition features into separate sets (first feature value set for daytime, second feature value set for nighttime), each optimized for specific segments of environmental conditions, thereby improving accuracy without requiring all features simultaneously.
Solution Approach 2:
The patent creates a universal recognition system that can function across multiple environments by preparing feature value sets with multi-functionality. Each feature value set is designed to handle multiple object recognition tasks within its environmental domain, allowing the same recognition framework to serve different lighting and temporal conditions effectively.
3Adaptability or versatility
If feature value sets are selected based on environmental information, then the adaptability improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary preparation of multiple feature value sets in advance, categorized by environmental conditions. The system pre-organizes first feature value sets for daytime conditions and second feature value sets for nighttime conditions, so that during actual operation, the processor only needs to compare current environmental parameters against predefined criteria and select the matching pre-prepared set, rather than creating or analyzing features in real-time.
Data Source
AI summary
A device and method for recognizing an object included in an input image are provided, the device for recognizing the object included in the input image includes a memory in which at least one program is stored; a camera configured to capture an environment around the device; and at least one processor configured to execute the at least one program to recognize an object included in an input image, wherein the at least one program includes instructions to: obtain the input image by controlling the camera; obtain information about the environment around the device that obtains the input image; determine, based on the information about the environment, a standard for using a plurality of feature value sets in a combined way, the plurality of feature value sets being used to recognize the object in the input image; and recognize the object included in the input image, by using the plurality of feature value sets based on the determined standard for using the plurality of feature value sets in the combined way.