Forensic Technology Center of Excellence

Introduction

Mapping Technologies for Crime Scenes

Mapping Technologies for Crime Scenes

Thursday, October 14th, 2021 | 1:00 - 2:00 PM ET
Duration: 1 hour

Traditionally, crime scene processing has involved manual measurements to construct diagrammatic representations of crime scenes. This is labor and time-intensive and does not necessarily yield a complete representation of any scene. Over the past few years, LiDAR-based scanners have seen increasing popularity in aiding investigators to make more complete digital, scaled, and three-dimensional representations of crime scenes.  While these systems offer a tremendous improvement over manual mapping, more recent advances in low-cost computing power and capture platforms, as well as AI/ML-augmented processing tools are now available. These tools offer the same or better ability to render crime scenes into highly accurate three-dimensional representations for a fraction of the cost and time. The webinar will focus on photogrammetry-based mapping tools to produce three-dimensional point clouds and meshes from drone-based and other image capture systems. 

Detailed Learning Objectives:
Upon completion, attendees will:
1.) Become familiar with the fundamental concepts of multi-ray photogrammetry and some of the processing tools available.
2.) Understand the potential image capture platforms, such as drones and 360° cameras, used to collect data for scene mapping.
3.) Learn the potential deliverable models and user interfaces for end user investigators to be able to use scene models.

Presenters:
Peter Stout, Ph.D. | CEO and President of the Houston Forensic Science Center

Register Here


Funding for this Forensic Technology Center of Excellence event has been provided by the National Institute of Justice.-

Please contact us at ForensicCOE@rti.org for any questions.

Each of our webinars is archived within about two weeks of the live date and will be posted on our website. Please subscribe to our newsletter for notifications.


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