Multi-Perspective Object Detection for Remote Criminal Analysis Using Drones

• Published in: IEEE geoscience and remote sensing letters Vol. 17; no. 7; pp. 1283 - 1286
• Main Authors: Araujo, Pompilio, Fontinele, Jefferson, Oliveira, Luciano
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cameras; Crime; Criminal scene investigation; Detection; Detectors; Drone aircraft; Drone vehicles; Drones; Image detection; intelligent drones; multi-perspective object detection; Object detection; Object recognition; Pattern recognition; Remote sensing; simultaneous localization and mapping (SLAM); Trajectory; Weapons
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2019.2940546

When a crime is committed, the associated site must be preserved and reviewed by a criminal expert. Some tools are commonly used to ensure the total registration of the crime scene with a minimal human interference. As a novel tool, we propose, here, an intelligent system that remotely recognizes and localizes objects considered as important evidences at a crime scene. Starting from a general viewpoint of the scene, a drone system defines trajectories through which the aerial vehicle performs a detailed search to record evidences. A multi-perspective detection approach is introduced by analyzing several images of the same object in order to improve the reliability of the object recognition. To the best of authors' knowledge, it is the first work on remote autonomous sensing of crime scenes. Experiments demonstrated an accuracy increase of 18.2% points, when using multi-perspective detection.