Date of Award
Santa Clara : Santa Clara University, 2018.
When an investigation team arrives to the scene, they only have a limited amount of time to gather as much evidence as they can. Evidence can include, but is not limited to: fingerprints, pictures/videos, blood samples, or any other biological evidence. Due to the limited amount of time, a few risks arise; they may not have collected enough evidence, the evidence itself may not have captured the full scope of the scene, and the possibility that the evidence itself may have been damaged or destroyed. Our aim is to develop a low-cost, customizable VR crime scene reconstructor. This software allows CSI as well as the court to revisit a crime scene by inputting only the necessary components of the crime in question based on previously collected data and witness accounts. Rather than using expensive cameras to capture an overly-realistic scene, a solution that is not computationally expensive is required because of not only the amount time it takes to render the setting, but also the requirement of high-end hardware to process the data. We propose a reconstructor that allows the user to construct the scene piece by piece, which lets the user understand the details individually rather than as a whole picture.We believe our VR simulator will be helpful not only in training CSI investigators but also in the courtroom by allowing juries to concentrate on the most pertinent details of a scene.
Tseng, Ellen and Wakaba, Ken, "Virtual Reality Sherlock: A Crime Scene Reconstructor" (2018). Computer Science and Engineering Senior Theses. 126.
Available for download on Monday, June 15, 2020