Living Body Detection Threshold Adjustment for Power Mode Switching
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Solution Overview
Problem
Existing image processing apparatuses with human body detection sensors face issues of erroneous power mode switching due to incorrect sensor adjustments, leading to wasteful energy consumption and potential misdetection of human presence, especially in environments where people frequently pass by without intending to use the device.
Innovation Solution
An image processing apparatus equipped with a living body detection unit that adjusts its detection threshold based on historical data of detection outputs and user operations, minimizing incorrect power mode switches by learning from usage patterns and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If a human body detection sensor is used to switch between power saving mode and normal mode, then power consumption is reduced, but erroneous detection causes wasteful energy consumption
Solution Approach 1:
The system records the operation history of the operation unit and uses this feedback to dynamically adjust the threshold value for human body detection. By comparing detection output against historically learned thresholds, the system avoids erroneous detection and unnecessary mode switching, thereby preventing wasteful energy consumption while maintaining power saving benefits
Solution Approach 2:
The image processing apparatus automatically learns and adapts to its installation environment by recording operation histories and autonomously determining appropriate threshold values. This self-adjusting capability eliminates the need for manual sensor orientation adjustment and enables the system to distinguish between passing pedestrians and actual users, reducing erroneous energy consumption
2Measurement precision
If the sensor orientation is made variable to improve detection accuracy, then detection precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical sensor orientation adjustment mechanism with an electronic/software-based solution. Instead of physically varying sensor directivity through motors or adjustable mounts, the system uses a camera to capture images and processes these images to determine threshold values based on operation histories. This substitution eliminates mechanical complexity while achieving adaptive detection accuracy
Solution Approach 2:
The system changes the detection parameter from fixed sensor orientation to dynamically adjustable threshold values. By recording operation histories and using these to determine optimal threshold values, the system achieves adaptive detection precision without requiring physical sensor reorientation, thereby avoiding increased device complexity
3Measurement precision
If manual adjustment of sensor orientation is required to improve detection accuracy, then detection precision is improved, but ease of operation deteriorates
Solution Approach 1:
The image processing apparatus performs automatic environment adaptation by autonomously recording operation histories and determining optimal threshold values without any user intervention. The system self-adjusts to distinguish between passing pedestrians and actual users, completely eliminating the need for manual sensor orientation adjustment and thereby maintaining high detection accuracy while ensuring ease of operation
4Measurement precision
If the detection threshold is lowered to improve detection sensitivity, then detection sensitivity is improved, but reliability of power mode switching deteriorates
Solution Approach 1:
The system uses operation history feedback to dynamically determine appropriate threshold values. By analyzing recorded operation patterns, the system adjusts thresholds to achieve optimal balance between detection sensitivity and switching reliability, preventing both missed detections and erroneous activations that would occur with fixed low thresholds
Solution Approach 2:
The detection threshold parameter is changed from a fixed low value to a dynamically adjusted value based on operation histories. The system records and analyzes operation patterns to determine optimal threshold values that maintain high detection sensitivity while ensuring reliable power mode switching by filtering out false positives from passing pedestrians
Data Source
AI summary
An image processing apparatus includes a living body detection unit configured to detect approaching of a living body based on a detection output depending on a distance to the living body, an operation unit configured to receive an operation command from a user, a history recording unit configured to record a history of a detection output of the living body detection unit and a history of an operation performed on the operation unit, and a determination unit configured to determine a threshold value of the detection output, the threshold value being used by the living body detection unit as a determination reference value in determining whether a living body is detected, the determination of the threshold value being made based on the history recorded in the history recording unit as to the detection output of the living body detection unit and as to the operation performed on the operation unit.