3D Object Recognition via Thingerprint Matching
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Solution Overview
Problem
Conventional image fingerprinting techniques struggle with identifying 3D objects, especially when viewed from different angles, as they rely on 2D feature points that become distorted and difficult to match, leading to high false positives and low detection rates.
Innovation Solution
The development of object recognition systems that incorporate 3D information and projective transformations, using multi-stage filtering approaches with Profile, Morphological, and Image features to create a 3D 'Thingerprint' of objects, allowing for robust matching across various viewpoints and reducing false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional 2D image fingerprinting techniques are used to identify objects, then the system is simple and easy to implement, but the detection rate is low and false positives are high when viewing 3D objects from different angles
Solution Approach 1:
The patent transitions from 2D image fingerprinting to 3D object recognition by introducing depth information and volumetric feature extraction. This dimensional change enables the system to handle objects viewed from different angles by creating viewpoint-invariant 3D representations, thereby improving detection rate while managing the increased complexity through structured processing pipelines.
2Reliability
If 3D information and projective transformations are incorporated into object recognition, then false positives are reduced and matching accuracy improves, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent implements a multi-stage processing pipeline that segments the object recognition task into distinct phases: initial 2D feature extraction, candidate generation, 3D model matching, and verification. This segmentation allows the system to achieve high reliability by progressively filtering candidates through increasingly sophisticated analysis, while managing computational complexity by distributing work across multiple specialized stages rather than requiring all processing in a single complex step.
3Measurement precision
If multi-stage filtering approaches with Profile, Morphological, and Image features are used, then object recognition accuracy improves significantly, but the processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary filtering using Profile and Morphological features before performing computationally intensive 3D Image feature matching. This preliminary action quickly eliminates obviously mismatched candidates based on simple geometric properties, thereby reducing the number of objects that require full 3D processing. This approach maintains high recognition accuracy by preserving all potentially matching candidates while significantly reducing average processing time through early elimination of non-matches.
Data Source
AI summary
Methods and arrangements involving portable user devices such smartphones and wearable electronic devices are disclosed, as well as other devices and sensors distributed within an ambient environment. Some arrangements enable a user to perform an object recognition process in a computationally- and time-efficient manner. Other arrangements enable users and other entities to, either individually or cooperatively, register or enroll physical objects into one or more object registries on which an object recognition process can be performed. Still other arrangements enable users and other entities to, either individually or cooperatively, associate registered or enrolled objects with one or more items of metadata. A great variety of other features and arrangements are also detailed.