Dynamic Image Analysis Method Selection for Accuracy and Resource Constraints
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Solution Overview
Problem
Existing image analysis techniques fail to properly analyze photographed images based on the image's state, required analysis accuracy, and computational resource constraints, as they do not consider these factors in their methods.
Innovation Solution
An information processing apparatus with a state deduction unit to determine the image's state and an analysis-method selection unit to choose the appropriate analysis method based on the deduced state, required accuracy, and constraint conditions, ensuring proper image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single fixed analysis method is used for all images, then the device complexity is reduced, but the analysis accuracy cannot be optimized according to different image states and constraints
Solution Approach 1:
The patent implements a dynamic analysis method selection mechanism where the system automatically chooses different analysis methods based on the deduced state of each photographed image and the given constraint conditions. This dynamic adaptation allows the system to optimize analysis accuracy for different image states (e.g., crowded vs. non-crowded, different lighting conditions) without requiring manual configuration, thereby resolving the contradiction between maintaining high analysis accuracy and avoiding excessive device complexity.
Solution Approach 2:
The system changes the parameters of the analysis process by selecting different analysis methods based on varying conditions. The state deduction unit identifies image characteristics, and the analysis method selection unit adjusts the analysis approach accordingly (e.g., selecting object detection methods with different parameters for crowded vs. non-crowded scenes). This parameter adaptation enables optimized analysis accuracy while keeping the overall system structure manageable.
2Measurement precision
If multiple analysis methods are prepared for different states, then the analysis accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent segments the analysis process into distinct components: a state deduction unit that identifies image characteristics, an analysis method selection unit that chooses appropriate methods, and multiple specialized analysis methods for different states. This segmentation allows the system to maintain multiple analysis methods without creating excessive overall complexity, as each component has a specific function and the selection logic automates the process.
Solution Approach 2:
The analysis method selection unit acts as an intermediary between the state deduction unit and the multiple analysis methods. It receives the deduced state, considers constraint conditions, and automatically selects the most appropriate analysis method. This intermediary layer manages the complexity of having multiple analysis methods by providing a systematic selection mechanism, thereby improving analysis accuracy without proportionally increasing device complexity.
3Productivity
If computational resources are allocated to other processes, then the productivity of the system is improved, but the available computational resources for image analysis are reduced
Solution Approach 1:
The patent applies partial action by selecting analysis methods that are sufficient for the required accuracy rather than always using the most computationally intensive methods. The system deduces the state of the photographed image and selects an appropriate analysis method that provides adequate accuracy while consuming fewer computational resources, thereby freeing up resources for other processes and improving overall system productivity.
Solution Approach 2:
The system changes computational resource allocation dynamically by selecting different analysis methods with varying resource requirements based on the image state and constraint conditions. For less complex images, lighter analysis methods are chosen, preserving computational resources for other processes. For complex images requiring higher accuracy, more resources are allocated temporarily. This adaptive parameter adjustment balances productivity and resource availability.
Data Source
AI summary
A state deduction unit (102) deduces a state presented in a photographed image (200). An analysis-method selection unit (105) selects as an analysis method for analyzing the photographed image (200), an analysis method from among a plurality of analysis methods, based on a deduced state which is the state deduced by the state deduction unit (102), required accuracy which is analysis accuracy required for analysis of the photographed image (200), and a constraint condition for analyzing the photographed image (200).