Camera Focus Area Selection for User-Intended Subject Detection
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Solution Overview
Problem
Existing image pickup systems struggle to accurately set focus detection areas based on user intent for subjects other than human faces, leading to potential misalignment with the desired focus area.
Innovation Solution
The system employs two detecting units to identify subject characteristics and scene characteristics, allowing for the selection of a focus detection area that aligns with user intent through machine-learned CNNs for subject and focus area detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the focus detection area is automatically set based on subject detection (e.g., eyes or face), then the system can operate autonomously without user intervention, but the focus area may not match the user's intended focus point in varying photographing scenes
Solution Approach 1:
The system dynamically switches between automatic focus area setting (based on subject detection) and manual user-specified focus area setting, depending on the photographing scene and user input. This dynamic adaptability resolves the contradiction by allowing the system to be highly automated in suitable scenarios while permitting user correction when automatic detection fails to match user intent.
Solution Approach 2:
The system provides feedback to the user about the automatically detected focus area (e.g., through display or indication), allowing the user to verify and adjust the focus area if it does not match their intention. This feedback loop enables the system to maintain high automation while ensuring focus area accuracy aligns with user expectations.
2Adaptability or versatility
If a single fixed method is used to set the focus detection area, then the device complexity is reduced, but the system cannot adapt to different photographing scenes and subject types
Solution Approach 1:
The focus area setting function is segmented into multiple independent detection methods: subject-based detection (e.g., eyes, face), scene-based detection, and user-specified detection. Each method operates independently and can be selected based on the photographing scenario, enabling adaptability without requiring a completely complex integrated system for every possible case.
Solution Approach 2:
The system implements a universal focus area setting mechanism that can handle multiple types of subjects (people, animals, objects) and various photographing scenes through a single integrated framework that selects among different detection methods. This multi-functional approach achieves high adaptability while avoiding the need for separate dedicated systems for each subject type.
Data Source
AI summary
An image pickup apparatus capable of setting a focus detection area to an area that a user wants to set for a detectable subject is provided. The image pickup apparatus comprising a first detecting unit configured to detect an area, which corresponds to at least a part of a subject area within an image and shows subject characteristics, as a first local area, a second detecting unit configured to detect an area, which corresponds to at least a part of the subject area and shows photographing scene characteristics, as a second local area, and a local area selecting unit configured to select one of the first local area and the second local area as an area to be focused according to information about a photographing scene of a subject in a case that both the first local area and the second local area are detected by the first detecting unit and the second detecting unit.