3D Trophy Scoring on Mobile Depth Sensors Without Connectivity
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Solution Overview
Problem
Traditional methods for measuring and scoring sporting trophies like deer antlers or large fish are highly manual, time-consuming, and prone to errors, requiring specialized expertise and impractical in field conditions due to limitations in time, lighting, and environmental factors.
Innovation Solution
Utilizing modern smartphones equipped with depth sensors and computational capabilities to acquire 3D point clouds of trophies, orient and model the features, and compute measurements and scores without network connectivity, enabling rapid and accurate scoring through techniques like LiDAR and photogrammetry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual measurement methods are used, then measurement accuracy can be maintained with simple tools, but the process becomes highly time-consuming and labor-intensive
Solution Approach 1:
The patent replaces manual mechanical measurement tools (tape measures, calipers) with automated optical scanning systems including LiDAR depth sensors and photogrammetry cameras. These systems capture three-dimensional point cloud data of trophies, enabling automated measurement extraction without manual intervention. The system processes point cloud data through algorithms that automatically identify anatomical landmarks and compute measurements, eliminating the time-consuming manual measurement process while maintaining accuracy.
Solution Approach 2:
The patent transforms physical trophy measurements into digital point cloud parameters. By capturing trophy geometry as three-dimensional point clouds with high-density spatial coordinates, the system enables rapid computational extraction of linear dimensions, surface areas, and volumes. This parameter transformation from physical to digital domain allows parallel processing of multiple measurement points simultaneously, dramatically increasing measurement productivity compared to sequential manual methods.
2Measurement precision
If manual measurement methods are used, then specialized expertise is required for accurate scoring, but the process becomes complex and error-prone
Solution Approach 1:
The patent implements self-service measurement through automated algorithms that independently identify trophy anatomical features and compute measurements without requiring expert operator intervention. The system uses machine learning models trained on trophy anatomy to automatically detect landmarks, orientation, and key measurement points from point cloud data. This automation eliminates the need for specialized measurement expertise while maintaining high scoring accuracy, as the algorithms consistently apply measurement protocols without human error.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system validates measurement results against anatomical constraints and scoring rules. The automated measurement process includes quality control checks that verify detected landmarks match expected anatomical patterns, and measurements are cross-validated against scoring formula requirements. This feedback loop ensures measurement precision while simplifying the process, as the system self-corrects potential errors without requiring expert review.
3Reliability
If comprehensive trophy measurements are taken manually, then complete scoring data can be obtained, but the process requires controlled environmental conditions
Solution Approach 1:
The patent replaces manual measurement systems that require controlled environments with automated optical scanning systems using LiDAR and photogrammetry. These systems actively illuminate and capture three-dimensional trophy geometry, enabling reliable measurements in varied lighting conditions including outdoor field environments. The point cloud capture technology is insensitive to ambient light variations, allowing comprehensive trophy documentation regardless of environmental lighting controls.
Solution Approach 2:
The patent employs dynamic measurement approaches where the scanning system can adapt to trophy positioning and environmental conditions in real-time. The photogrammetry and LiDAR systems capture data from multiple angles and distances, compensating for suboptimal positioning or environmental factors. The system processes point cloud data to reconstruct accurate three-dimensional trophy models even when captured in challenging field conditions, maintaining measurement reliability without requiring controlled environments.
4Productivity
If automated 3D scanning systems are used, then measurement speed and accuracy are improved, but the device complexity increases
Solution Approach 1:
The patent leverages multi-functional mobile devices that integrate depth sensors (LiDAR), photogrammetry cameras, processors, and display systems into a single universal platform. This single device performs multiple functions: capturing three-dimensional point cloud data, processing measurements, applying scoring formulas, and displaying results. By consolidating what would otherwise require separate specialized equipment into one universal device, the system achieves high automation productivity without proportionally increasing overall system complexity.
Solution Approach 2:
The patent creates digital three-dimensional point cloud copies of physical trophies, enabling all subsequent measurement and scoring operations to be performed on the digital replica rather than the physical object. This digital copying approach allows the complex processing to occur in the digital domain using software algorithms, separating the simple data capture phase from the complex analysis phase. The point cloud copy serves as a virtual model that can be repeatedly measured without additional physical intervention, reducing overall system complexity while maintaining automation capabilities.
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
Enables fast, accurate, and reliable measurement and scoring of sporting trophies in-field, reducing human error and time consumption, and allowing immediate feedback and data storage or sharing without reliance on internet connectivity.
Implementation Method 1
using the capabilities of modern smartphones. This field involves the use of technologies like LiDAR and photogrammetry to create 3D point clouds (3DPC) of the trophies
Implementation Method 2
using the capabilities of modern smartphones. This field involves the use of technologies like LiDAR and photogrammetry to create 3D point clouds (3DPC) of the trophies
Data Source
AI summary
An approach is provided for automated sporting trophy measurement and scoring. The approach involves, for instance, acquiring, by a depth sensor of a mobile device, sensor data representing a three-dimensional (3D) point cloud of a trophy animal including an animal feature. The approach also involves detecting, by one or more processors of the mobile device, points of the 3D point cloud corresponding the animal feature, and orienting the animal feature of interest to a designated measurement orientation. The approach further involves building a model of the animal feature comprising a skeleton graph with nodes and edges. The approach further involves computing one or more measurements of the animal feature from the model and the point cloud, and computing a score from the one or more measurements on the mobile device without network connectivity.