3D Object Scan Using Infrared Sensor Data
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Solution Overview
Problem
Existing three-dimensional scanning technologies face challenges in generating accurate models, particularly when scanning objects in contact with human body parts, as they struggle to differentiate and exclude irrelevant human body features like hands or backgrounds, leading to confusion and reduced accuracy.
Innovation Solution
The system utilizes data from infrared sensors to identify and exclude human body parts by preprocessing, reconstructing, and post-processing the data, improving camera tracking and depth data accuracy, and combining IR data with RGB and depth data for robust image generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional three-dimensional scanning is used to scan objects in contact with human body parts, then the scanning process is simple, but the accuracy is reduced due to inability to differentiate and exclude irrelevant human body features
Solution Approach 1:
The patent segments the scanning data into different categories: object data, human body part data, and background data. By separating these components, the system can selectively process and exclude irrelevant elements (hands, arms, background) while retaining the target object, thereby improving scanning accuracy without requiring complex manual intervention
Solution Approach 2:
The patent introduces infrared sensors as an intermediary component that captures thermal radiation data. This intermediary data source enables the system to differentiate between human body parts and the target object based on thermal signatures, allowing accurate exclusion of irrelevant elements while maintaining system feasibility
2Measurement precision
If infrared sensors are added to differentiate human body parts, then scanning accuracy is improved, but device complexity increases
Solution Approach 1:
The patent merges infrared sensor data with traditional depth sensor data and RGB camera data into a unified processing framework. By combining these data sources and processing them together through a single system architecture, the patent achieves improved depth data accuracy while minimizing the increase in device complexity through integrated rather than separate processing systems
Solution Approach 2:
The patent creates a universal processing system that handles multiple data types (infrared, depth, RGB) through a single unified algorithm framework. This multi-functional approach allows the system to process different sensor inputs using the same exclusion logic, reducing the need for separate processing pipelines and thereby limiting the complexity increase
3Manufacturing precision
If human body parts are included in the scan, then the scanning process is simple, but the three-dimensional model quality is reduced
Solution Approach 1:
The patent implements self-service functionality where the system automatically identifies and excludes human body parts and background elements without requiring manual intervention. The exclusion algorithm autonomously processes the multi-source data, identifies irrelevant elements based on thermal and spatial characteristics, and removes them from the final model, thereby maintaining operational simplicity while improving model quality
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
This approach enhances the quality of three-dimensional models by accurately identifying and removing human body parts and backgrounds, improving camera tracking, and increasing the confidence and accuracy of depth data, resulting in more reliable and detailed scans.
Implementation Method 1
obtain infrared data regarding the object using an infrared sensor
Data Source
AI summary
Described herein is a system and method for scanning a three-dimensional object using data from an infrared sensor. The data can be used during preprocessing, reconstructing and/or post processing of generation of a three-dimensional model. Data from an infrared sensor and data from a sensor (e.g., RGB sensor, a depth sensor, a camera, a scanner, a digital camera, a digital video camera, a web camera, depth sensor, etc.) can be utilized to generate a three-dimensional model of the three-dimensional object. For example, the data from the infrared sensor can be utilized to identify an item and to exclude the identified item from the generated three-dimensional model.