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Open Access Special Topic Issue
Exploring the Application Prospects of Artificial Intelligence Technology in the Identification and Reconstruction of Crime Scene Elements
Forensic Science and Technology 2025, 50(1): 16-20
Published: 15 February 2025
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This paper explores the progress of artificial intelligence technology in the identification and reconstruction of crime scene elements. With the development of information technology, there are challenges faced by crime scene element identification and reconstruction. The paper discusses the application benefits of artificial intelligence, the relevant applications of artificial intelligence in forensic examination, and outlines the key steps of artificial intelligence in crime scene element identification and reconstruction, to explore the possibility of applying this method to crime scene element identification and reconstruction. Finally, the paper looks forward to the future development of artificial intelligence in forensic examination and suggests that it may play an important role in improving the intelligence level of crime scene examination and increasing the efficiency of case investigation. It is hoped that relevant research will provide a solution for the technical transformation of crime scene examiners and lay a foundation for the intelligent and digital development of forensic technology.

Open Access Research Article Issue
Research on Air-ground Integration Method for Constructing Realistic 3D Models of High Falling Incident Scenes
Forensic Science and Technology 2025, 50(5): 496-503
Published: 18 September 2024
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This study explored the utilization of low-altitude unmanned aerial vehicle (UAV) imagery combined with ground-based handheld photography to create a multi-scale, variable-resolution 3D realistic model of high falling incident scenes. Initially, a low-altitude UAV is employed to capture imagery data of the orientation, general overview, and fall space of the high falling incident site. Subsequently, a digital single-lens reflex (DSLR) camera is utilized to obtain detailed image data of key areas such as the starting and ending points of the fall. In the SMART 3D reconstruction software, feature points are marked and matched between the UAV imagery and the handheld camera images, aiming to rigidly correlate the aerial and ground data, thereby fusing these diverse sources to create a refined 3D model. The results demonstrate that the 3D model, constructed through the fusion of the two data sources, offers a multi-scale, comprehensive representation of the high falling incident scene. It enables users to observe both the overall orientation and layout from a distance, as well as to scrutinize key areas and detailed features up close. This technical methodology provides a direct and authentic representation of the location, texture, size, and other physical attributes of trace evidence at the scene. It offers a novel means for digitally documenting and preserving the high falling incident scene, which can then aid in reconstructing the fall sequence and enable accurate determination of the case’s nature.

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