Mobile Camera Face Detection Using Distance Tolerance
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Solution Overview
Problem
Existing mobile communication devices face challenges in accurately controlling camera functions, particularly in identifying and tracking user faces amidst background changes, which affects the reliability of eye-tracking techniques.
Innovation Solution
A method and device using a user's distance specifying algorithm that involves receiving input images, determining candidate faces, extracting data with minimum distance information, and comparing it within a tolerance range to accurately track user faces regardless of background changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional face detection methods are used, then the system can identify faces, but the accuracy deteriorates when background changes occur
Solution Approach 1:
The patent introduces distance information as an intermediary parameter between the camera and the user's face. By incorporating this spatial dimension, the system can distinguish the user's face from background elements based on their relative distances, thereby maintaining accurate face detection across varying background conditions.
Solution Approach 2:
The patent transitions from two-dimensional image processing to three-dimensional spatial reasoning by adding distance information. This dimensional enhancement allows the system to perceive depth and differentiate between foreground (user's face) and background elements, resolving the accuracy issue under background changes.
2Reliability
If eye-tracking is implemented without distance specification, then the system operates simply, but the reliability deteriorates
Solution Approach 1:
The system utilizes the camera's existing depth information capabilities to automatically obtain distance data without requiring additional external devices or complex manual configuration. The camera itself serves the dual purpose of capturing images and providing distance measurements, thereby improving reliability while minimizing added complexity.
3Measurement precision
If background elements are not removed, then the processing is simple, but the measurement precision of user location deteriorates
Solution Approach 1:
The patent extracts and utilizes distance information as a key feature to separate the user's face from background elements. By focusing on the depth dimension and extracting distance data, the system can identify and track the user's face location with high precision without requiring complex background removal algorithms.
Data Source
AI summary
A method for controlling a mobile communication device using a user's distance specifying algorithm, the method comprises a first process of receiving an input image from a camera to generate first data; a second process of determining whether there is a candidate group that can be determined as a face using the first data and second data including a user's distance information; a third process of extracting, if there is a candidate group that can be determined as a face, from a plurality of third data including location information of the candidate group, fourth data having a minimum distance between a center of the first data and a center of the third data; and a fourth process of comparing the fourth data with a predetermined user's distance to determine whether it has a value within a tolerance range.