Volumetric Object Tracking via Depth Sensor Profiles
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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 information related to moving objects.
Innovation Solution
The use of a volumetric sensor, such as a depth sensor, to calculate a volumetric representation of objects in real-time, combined with metadata from other sensors like video cameras, microphones, and chemical sensors, to assign a unique volumetric profile and store it in a database for identification and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If video cameras are used to track individuals, then visual information can be captured, but unique identification and accurate tracking of each individual is not provided
Solution Approach 1:
The patent transitions from 2D video camera images to 3D volumetric representations by introducing depth information through depth sensors. This dimensional change enables the system to capture volumetric attributes (width, height, depth) that provide unique identification characteristics for each individual, resolving the inability of 2D cameras to provide unique identification.
2Reliability
If current object tracking mechanisms are used, then tracking functionality is provided, but the systems are costly and computationally expensive
Solution Approach 1:
The patent replaces complex mechanical tracking systems with a sensor-based volumetric detection system. By using depth sensors to directly measure volumetric attributes and creating volumetric profiles, the system achieves accurate tracking without the computational burden and cost of traditional video analysis and tracking algorithms.
3Shape
If volumetric representations are created using prior art methods, then 3D object representation is achieved, but foreground and background voxels must be assigned to silhouettes which adds complexity
Solution Approach 1:
The patent extracts only the essential volumetric attributes (width, height, depth, centroid position) needed for identification and tracking, rather than creating complete volumetric models with foreground-background voxel assignment. This extraction approach maintains accurate 3D representation while eliminating the complex silhouette segmentation process.
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, enabling efficient identification and metadata annotation, improving upon the limitations of prior art by using depth sensors and other sensors to determine object contours and physical attributes.
Implementation Method 1
a depth sensor to calculate a volumetric representation of objects in real-time
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.