Automatic Image Capture via Position Condition Detection
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Solution Overview
Problem
Existing image capture technologies fail to automatically capture images when an object enters the scene quickly, as they require user intervention or rely on predefined conditions that are not adaptable to dynamic scenarios.
Innovation Solution
A method that allows users to define position conditions for automatic image capture based on user-input gestures and kinematic parameters, enabling the capture of objects entering the scene at specific positions or displacements, with pre-set camera settings for optimal image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing image capture technologies are used, then user intervention is required for image capture, but automatic capture of quickly entering objects is not achieved
Solution Approach 1:
The system performs preliminary actions by pre-defining capture regions and conditions before the object enters the scene. The processor continuously monitors the captured image data against these pre-set conditions, enabling automatic capture when conditions are met without requiring real-time user intervention.
Solution Approach 2:
The system serves itself by automatically detecting when an object enters the predefined capture region and triggering the image capture process autonomously. The processor compares incoming image data with stored position conditions and executes capture decisions without external user input, making the system self-sufficient.
2Adaptability or versatility
If predefined capture conditions are used, then capture triggers are simple, but adaptability to dynamic scenarios is limited
Solution Approach 1:
The system implements dynamic adaptability by allowing capture conditions to be defined in terms of object movement and position changes rather than static parameters. The processor evaluates kinematic parameters such as object entry into capture regions, enabling the system to adapt to various dynamic scenarios including objects moving at different speeds and trajectories.
Solution Approach 2:
The system achieves universality by designing a flexible capture condition framework that can handle multiple types of scenarios through a unified approach. The same processor-based system can detect different object types, various capture regions, and multiple kinematic conditions, making it versatile across diverse dynamic situations without requiring scenario-specific hardware.
3Measurement precision
If continuous image monitoring is performed, then object entry detection is accurate, but processing time and energy consumption increase
Solution Approach 1:
The system segments the image processing task by dividing the overall scene into multiple predefined capture regions. Instead of analyzing the entire image continuously, the processor focuses monitoring efforts on specific regions where object entry is most likely to occur, reducing overall processing time while maintaining detection accuracy for objects entering these regions.
Solution Approach 2:
The system applies local quality by concentrating processing resources on specific capture regions rather than uniformly processing the entire image. The processor performs detailed analysis only in regions where objects are detected or where capture conditions are defined, reducing unnecessary processing in areas without potential targets while maintaining high detection precision where needed.
Data Source
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AI summary
An apparatus comprising: means for processing, at a first time, a user-input to determine a position condition defined in respect of an object that is yet to be included in a sensed image; and means for automatically capturing, after the first time, a sensed image including a first object not included in the sensed image at the first time, in response to determination that the user-input position condition is satisfied in respect of the first object.