Head Recognition Using Depth-Aware Elliptical Hough Transform
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Solution Overview
Problem
Conventional image recognition systems, especially 2D systems, face challenges in accurately recognizing human heads due to lack of depth perception, leading to flawed gesture recognition, limited input range, and high false positive rates, particularly in distinguishing the user from the background.
Innovation Solution
A method that utilizes depth information from 3D imaging systems to calculate the major and minor radius sizes of an ellipse framing the human head, combined with an elliptical Hough transform and additional detection methods, to enhance computation speed and reduce false positives by considering the head's depth measurement and using fuzzy ellipses in an accumulator array.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2D image recognition systems are used to detect human heads, then the system complexity is low, but the detection accuracy and reliability are poor due to lack of depth perception
Solution Approach 1:
The patent transitions from 2D image recognition to 3D depth-aware recognition by integrating depth maps with color images. The depth information provides the missing dimensional data, enabling accurate head detection and segmentation by distinguishing foreground subjects from background based on depth cues rather than relying solely on 2D color and texture information.
2Productivity
If conventional 2D image recognition is used, then the computation speed is fast, but the gesture recognition is flawed and limited in range
Solution Approach 1:
The patent merges color image data with depth map data into a unified 3D recognition framework. By combining these two data sources, the system maintains computational efficiency while significantly improving gesture and head detection reliability, as the depth information provides additional cues for distinguishing valid gestures from background artifacts.
3Measurement precision
If 2D projection-based recognition is used, then the system is simple to operate, but it cannot separate the user from the background effectively
Solution Approach 1:
The patent adds the depth dimension to the detection process, using depth maps to differentiate between foreground users and background elements. This dimensional enhancement allows the system to separate user from background effectively by identifying depth discontinuities and depth-consistent regions, without requiring complex multi-camera setups.
4Adaptability or versatility
If physical input devices are used for user interaction, then the input method is reliable, but the user experience lacks realism and has limited input signals
Solution Approach 1:
The patent creates a virtual copy of the user's physical head and gestures in the 3D digital environment. By tracking the real user's head position, orientation, and gestures through depth-sensing technology, the system translates physical movements into virtual avatar actions, providing a realistic and versatile input method that maintains reliability through accurate 3D pose estimation.
Data Source
AI summary
Described herein is a method for recognizing a human head in a source image. The method comprises detecting a contour of at least part of a human body in the source image, calculating a depth of the human body in the source image. From the source image, a major radius size and a minor radius size of an ellipse corresponding to a human head at the depth is calculated, and, for at least several of a set of pixels of the detected contour, generating in an accumulator array at least one segment of an ellipse centered on the position of the contour pixel and having the major and minor radius sizes. Positions of local intensity maxima in the accumulator array are selected as corresponding to positions of the human head candidates in the source image.