3D Object Tracking via 2D Feature Point Database
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Solution Overview
Problem
Conventional methods for tracking three-dimensional objects are limited by the need for exact geometric knowledge, making them unsuitable for complex natural objects and being too costly and complex for mass market deployment, especially when virtual models do not exist.
Innovation Solution
A method involving constructing a database of two-dimensional images of a 3D object using a tracking background with known patterns, extracting and comparing feature points between images to estimate the pose of the object, allowing for tracking without requiring detailed 3D modeling skills or expensive equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional model-based tracking methods are used, then tracking accuracy for simple objects is improved, but applicability to complex natural 3D objects deteriorates
Solution Approach 1:
The patent creates a database of 2D images from multiple viewing angles of the 3D object, storing these as reference templates. During tracking, the system compares feature points from captured images against this database of copies, enabling recognition of complex natural objects without requiring detailed 3D geometric models. This copying approach allows the system to handle diverse object shapes while maintaining tracking accuracy.
2Manufacturing precision
If three dimensional scanners are used to acquire virtual models, then model accuracy is improved, but system complexity and cost increase
Solution Approach 1:
Instead of using expensive three-dimensional scanners and specialized 3D modeling equipment, the patent employs standard 2D image capture devices to create sufficient tracking models. The system captures multiple 2D images from different angles and processes them through automated feature extraction and database construction, replacing costly specialized equipment with affordable, readily available technology while achieving adequate model accuracy for tracking purposes.
Solution Approach 2:
The patent replaces the mechanical three-dimensional scanning system with an optical 2D image capture system combined with computational processing. Instead of physically scanning objects with specialized hardware, the system uses standard cameras to capture images and employs computer vision algorithms for feature extraction, database construction, and pose estimation, significantly reducing device complexity and cost.
3Manufacturing precision
If conventional 3D modeling processes are used, then model quality is improved, but ease of operation deteriorates
Solution Approach 1:
The patent implements automated feature extraction and database construction processes that require minimal user intervention. The system automatically extracts feature points from captured 2D images, matches them across multiple views, constructs the image database, and prepares tracking models without requiring specialized 3D modeling skills. This self-service approach enables users to deploy tracking systems for complex natural objects without expert knowledge, significantly improving ease of operation while maintaining model quality.
Data Source
AI summary
Method and apparatus for tracking three-dimensional (3D) objects are disclosed. In one embodiment, a method of tracking a 3D object includes constructing a database to store a set of two-dimensional (2D) images of the 3D object using a tracking background, where the tracking background includes at least one known pattern, receiving a tracking image, determining whether the tracking image matches at least one image in the database in accordance with feature points of the tracking image, and providing information about the tracking image in respond to the tracking image matches the at least one image in the database. The method of constructing a database also includes capturing the set of 2D images of the 3D object with the tracking background, extracting a set of feature points from each 2D image, and storing the set of feature points in the database.