Single-LiDAR Motion Capture With AI Inference for Real-Time Accuracy

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Solution Overview

Problem

Existing motion capture technologies require multiple cameras or sensors, high setup costs, and lengthy preparation processes, making them impractical for real-time motion data capture and limiting their commercial viability.

Innovation Solution

A markerless motion capture system using a single LiDAR device to obtain point cloud data and infer motion data in real-time through an AI-based inference model, reducing setup costs and time while improving data quality and accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If multiple cameras or sensors are used for motion capture, then measurement precision is improved, but device complexity increases

Engineering Contradiction:

Improvemotion data accuracyVSAvoidnumber of cameras/sensors

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent combines multiple camera functions into a single LiDAR device that can capture both depth information and motion data. The LiDAR device integrates the functionality of multiple cameras by using a single sensor to obtain point cloud data that represents three-dimensional spatial information, thereby reducing device complexity while maintaining measurement precision.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces an AI-based inference model as an intermediary between the LiDAR device and the final motion data output. This intermediary processes the point cloud data and generates accurate motion data through neural network computations, compensating for the reduced hardware complexity with intelligent processing.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If multiple devices are installed for markerless motion capture, then measurement precision is improved, but installation space requirements increase

Engineering Contradiction:

Improvemotion detection accuracyVSAvoidinstallation space

Core Design Contradiction:

Measurement precisionVSArea of stationary object

Solution Approach 1:

The patent merges the functions of multiple cameras into a single LiDAR device, eliminating the need for multiple devices to be installed simultaneously. This consolidation significantly reduces the installation space requirements while maintaining the ability to capture accurate three-dimensional motion data through point cloud processing.

Inventive Principle:

Principle #5Merging (Combining)

3Measurement precision

If calibration process is performed for multiple devices, then measurement precision is improved, but preparation time increases

Engineering Contradiction:

Improvedata alignment accuracyVSAvoidpreparation time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent extracts the calibration function from the traditional multi-device setup and integrates it into the AI-based inference model. The model automatically performs alignment and calibration through neural network processing of point cloud data, eliminating the need for manual calibration procedures and significantly reducing preparation time.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent replaces the mechanical calibration process (physically adjusting and aligning multiple devices) with an automated AI-based calibration system. The neural network model performs virtual alignment and calibration computations, substituting manual mechanical adjustments with intelligent algorithms that achieve similar or better precision without the time-consuming physical setup.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Measurement precision

If point cloud data is processed to generate motion data, then measurement precision is improved, but processing time increases

Engineering Contradiction:

Improvemotion data qualityVSAvoiddata processing cycle

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces traditional mechanical image processing methods with AI-based neural network inference. The model directly processes point cloud data through neural network computations to generate motion data, achieving faster processing speeds compared to traditional methods while maintaining or improving measurement precision through intelligent feature extraction and motion inference.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

The system significantly reduces capture time and costs, enhances motion data quality, and enables high-resolution, real-time motion data generation.

Implementation Method 1

A motion capture system using a single LiDAR device to obtain point cloud data

Methodology Applied

Scientific EffectLight: Light

Implementation Method 2

LiDAR device obtains point cloud data related to the object at a first time point and at a second time point

Methodology Applied

Scientific EffectTime of Flight: Time of Flight

Data Source

PatentUS12601839B2Real-time motion capture system using single LiDAR device

Publication Date: 2026.04.14 MOVIN INC

AI summary

A real time motion capture system using a single LiDAR device is proposed, and more specifically, there is provided a system configured to capture movement of a person by using the single LiDAR device, obtain point cloud data, and analyze the obtained point cloud data, so as to generate motion data in real time for expressing the movement of the person.