3D Volumetric Object Tracking with Depth Sensor Annotation
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Solution Overview
Problem
Current object tracking mechanisms are costly, inaccurate, and computationally expensive, and lack the ability to provide unique identification and annotation of moving objects with metadata.
Innovation Solution
The use of a volumetric sensor, such as a depth sensor, in conjunction with other sensors like video cameras, microphones, and thermal sensors, to calculate a volumetric representation of objects and annotate them with metadata, enabling unique identification and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If video cameras are used to track individuals, then object tracking capability is provided, but unique identification and annotation capability are lost
Solution Approach 1:
The patent transitions from 2D video camera tracking to 3D volumetric sensing, adding a depth dimension to object representation. This dimensional change enables unique identification through volumetric profiles while maintaining tracking capability, as the 3D spatial information provides additional discriminative features for distinguishing objects.
Solution Approach 2:
The system changes the parameter space from 2D image coordinates to 3D volumetric parameters including depth, volume, and spatial distribution. By representing objects in terms of volumetric attributes rather than 2D pixel data, the system achieves both reliable tracking and unique identification through multi-dimensional parameter comparison.
2Measurement precision
If complex tracking systems are implemented to provide accurate object tracking, then tracking precision is improved, but system cost and computational expense increase
Solution Approach 1:
The patent replaces complex mechanical and computational tracking systems with a volumetric sensing approach that captures 3D spatial information directly. This substitution reduces computational complexity by working with native 3D data from depth sensors rather than processing 2D video frames through complex algorithms, while maintaining high tracking precision through direct volumetric measurement.
3Measurement precision
If volumetric sensors are used to calculate 3D representations, then object identification accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system extracts and stores only the essential volumetric parameters needed for identification, such as volume, centroid position, and key spatial dimensions, rather than processing complete 3D point clouds. This extraction approach maintains high identification accuracy by preserving critical geometric features while reducing data processing complexity through selective parameter retention.
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 provides an inexpensive and accurate method for tracking and annotating moving objects with unique volumetric profiles, including metadata like chemical information, enhancing object identification and tracking efficiency.
Implementation Method 1
time-of-flight sensors from which depth can be calculated
Data Source
AI summary
A system and method for tracking and annotating objects in a 3D model is disclosed. The method includes receiving a signal feed from a group of sensors including at least one depth sensor, determining a reference signal feed from the signal feed, determining a volumetric representation of at least one object not present in the reference signal feed, assigning a unique volumetric profile to at least one object, and/or storing the unique volumetric profile in an object database. The signal feed may include at least one 3D area of interest. Also, the unique volumetric profile may include a unique volumetric id obtained from a group of attributes. The unique volumetric profile may include at least a unique volumetric position and a unique volumetric centroid. The group of sensors may further include video cameras, thermal, and chemical sensors.