3D Head Pose Estimation Using Depth Data and PSO-ICP Optimization

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Solution Overview

Problem

Conventional RGB-based head pose estimation techniques produce unsatisfactory results in poor lighting conditions and require lengthy calibration sequences, leading to inaccurate head pose estimation.

Innovation Solution

The method involves acquiring depth data and using a combination of iterative closest point (ICP) and particle swarm optimization (PSO) techniques to estimate the head pose, with a 3D reference model being iteratively refined based on depth data, eliminating the need for initial calibration and improving accuracy regardless of lighting conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If RGB-based head pose estimation techniques are used, then the system can operate with standard cameras, but the accuracy deteriorates in poor lighting conditions

Engineering Contradiction:

Improvecamera compatibilityVSAvoidhead pose estimation accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent replaces RGB optical-based head pose estimation with depth-based estimation using time-of-flight or structured light depth cameras. This substitution of the sensing mechanism eliminates dependence on visible light conditions, allowing accurate head pose estimation in poor lighting where RGB cameras fail.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If rotation-specific classifiers are used for head pose estimation, then the system can achieve user-specific accuracy, but the calibration time increases

Engineering Contradiction:

Improveuser-specific head pose accuracyVSAvoidcalibration sequence duration

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent implements self-service by enabling the system to automatically adapt to individual users without requiring manual calibration. The depth-based approach with particle swarm optimization and ICP allows the system to automatically learn and adjust to user-specific head geometry and characteristics, eliminating the need for time-consuming calibration sequences while maintaining user-specific accuracy.

Inventive Principle:

Principle #25Self-service

3Measurement precision

If RGB images are registered to 3D templates, then the system can achieve head pose estimation, but the process fails under illumination variations

Engineering Contradiction:

Improvehead pose estimation capabilityVSAvoidrobustness to lighting conditions

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent replaces the RGB image registration process with direct depth data processing. Instead of converting depth to RGB and performing template registration (which is sensitive to lighting), the system operates directly in depth space using point cloud data and ICP algorithms, which are inherently robust to illumination variations since depth information is independent of lighting conditions.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Ease of manufacture

If conventional RGB-based techniques are used, then the system implementation is straightforward, but occlusions and shadows cause estimation errors

Engineering Contradiction:

Improvesystem implementation simplicityVSAvoidhead pose estimation accuracy

Core Design Contradiction:

Ease of manufactureVSMeasurement precision

Solution Approach 1:

The patent substitutes RGB image processing with depth-based processing. Depth cameras capture three-dimensional spatial information that is not affected by occlusions or shadows in the same way RGB images are. The depth data provides direct geometric measurements that remain reliable even when parts of the face are occluded or in shadow, thereby maintaining implementation simplicity while improving accuracy.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS10311589B2Model-based three-dimensional head pose estimation

Publication Date: 2019.06.04 NVIDIA CORP

AI summary

One embodiment of the present invention sets forth a technique for estimating a head pose of a user. The technique includes acquiring depth data associated with a head of the user and initializing each particle included in a set of particles with a different candidate head pose. The technique further includes performing one or more optimization passes that include performing at least one iterative closest point (ICP) iteration for each particle and performing at least one particle swarm optimization (PSO) iteration. Each ICP iteration includes rendering the three-dimensional reference model based on the candidate head pose associated with the particle and comparing the three-dimensional reference model to the depth data. Each PSO iteration comprises updating a global best head pose associated with the set of particles and modifying at least one candidate head pose. The technique further includes modifying a shape of the three-dimensional reference model based on depth data.