A Solution for Crime Scene Reconstruction using Time-of-Flight Cameras

Abstract

In this work, we propose a method for three-dimensional (3D) reconstruction of wide crime scene, based on a Simultaneous Localization and Mapping (SLAM) approach. We used a Kinect V2 Time-of-Flight (TOF) RGB-D camera to provide colored dense point clouds at a 30 Hz frequency. This device is moved freely (6 degrees of freedom) during the scene exploration. The implemented SLAM solution aligns successive point clouds using an 3D keypoints description and matching approach. This type of approach exploits both colorimetric and geometrical information, and permits reconstruction under poor illumination conditions. Our solution has been tested for indoor crime scene and outdoor archaeological site reconstruction, returning a mean error around one centimeter. It is less precise than environmental laser scanner solution, but more practical and portable as well as less cumbersome. Also, the hardware is definitively cheaper.

Overlapping Shoeprint Detection by Edge Detection and Deep Learning

“…A shoeprint represents the textured image left behind when the sole of a shoe makes contact with a surface in the natural environment [4]. In forensic investigations involving shoeprints left behind at the scene of a crime, a clear and complete texture is important for accurate identification [5,6]. However, in reality, there are frequent instances where two or even multiple textures overlap, leading to a loss of information.…”