Automated Evidence Marker Identification in 3D Point Clouds
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Solution Overview
Problem
Current methods for documenting crime scenes using evidence markers in 3D point clouds are inefficient due to the manual process of locating and marking hundreds of markers, which is time-consuming and prone to errors.
Innovation Solution
A system and method that automatically identifies evidence markers in a 3D point cloud using photogrammetric symbols, allowing for the determination of their location and attributes, and associates relevant data with the markers, thereby streamlining the documentation process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification and marking of evidence markers is performed, then accuracy of marker location can be maintained, but time consumption increases significantly
Solution Approach 1:
The patent replaces the manual mechanical process of locating and marking evidence markers with an automated computer vision system. The system uses image processing algorithms to automatically detect photogrammetric symbols in 3D point cloud data, extract marker locations, and associate them with evidence items. This substitution of manual mechanical operations with automated computational methods resolves the contradiction by maintaining location accuracy through precise algorithmic detection while dramatically reducing documentation time.
2Productivity
If automated identification of evidence markers is implemented, then productivity increases, but system complexity increases
Solution Approach 1:
The patent implements a multi-functional integrated system that performs multiple tasks: 3D scanning of the crime scene, generation of point cloud data, automatic detection of photogrammetric symbols, extraction of marker locations, and association with evidence items. By combining these functions into a single automated workflow, the system achieves high productivity while managing complexity through integration rather than separate manual operations for each function.
Solution Approach 2:
The system uses photogrammetric symbols as standardized visual copies or representations of evidence markers. These symbols are captured in 3D point cloud data and serve as identifiable templates that the automated system can recognize and process. This copying approach allows the system to identify markers without requiring complex interpretation of varied marker appearances, thus improving productivity while controlling system complexity through pattern recognition.
3Measurement precision
If detailed 3D scanning is performed to capture all scene elements, then measurement precision is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts only the relevant information from the comprehensive 3D point cloud data - specifically, the photogrammetric symbols associated with evidence markers. Rather than processing and analyzing all points in the detailed 3D scan, the system selectively identifies and extracts marker locations and attributes. This extraction approach maintains measurement precision by preserving the detailed 3D data for accurate location determination while reducing processing complexity by focusing computational resources on identifying specific marker features rather than analyzing the entire scene data set.
Data Source
AI summary
A system and method for documenting a scene having evidence markers is provided. The method includes placing the evidence markers in the scene. A plurality of 3D coordinates of points are measured on surfaces in the environment, a first portion of the plurality of 3D coordinates being on a first evidence marker of the evidence markers, the evidence marker having a photogrammetric symbol on one surface. A point cloud is generated from the plurality of 3D coordinates. The first evidence marker in the point cloud based is automatically identified at least in part on the photogrammetric symbol. The location and at least one attribute of the evidence marker are stored.