# Comparative Analysis of LiDAR and Photogrammetry for 3D Crime Scene Reconstruction
## 2 Related Work  
### Applications of LiDAR in Crime Scene Reconstruction  
The study by [PERSON] et al. [3] evaluated how accurately handheld LiDAR devices can be used to reconstruct crash scenes. The generated point cloud data were extracted from devices like the iPad Pro (Apple Inc., Cupertino, CA, USA), the FARO Focus 3D X330 (FARO Inc., Lake Mary, FL, USA), and TLS Trimble TX8 (Trimble Inc., Westminster, CO, USA) to analyze vehicle damage. Their results were promising, showing that the iPad Pro scanning took around 15 min, compared to 3 h for the other two devices. It also had a maximum root mean square error (RMSE) of 3 cm. This level of precision falls within an acceptable range for reconstructing crash scenes. Another study involving the iPad Pro tablet was conducted by [PERSON] et al. [4]. Three-dimensional forensic science was the focus of the study, which utilized 3D scanning and modeling to assist the investigation. The iPad model used was 11 Pro, while photogrammetry software, Scaniverse Pro Version 1.4.0, was used to construct 3D wireframe models. According to the researchers, 3D tools provide advantages in court by presenting facts appealingly and convincingly. However, they still do not substitute traditional methods but instead complement them. [PERSON] et al. [19] focused on testing the Recon-3D application on an iPhone 13 Pro to capture a simulated accident and crime scene. The findings indicate that utilizing iPhone LiDAR with the Recon-3D app for reconstructing forensic crime scenes yielded 3D documentation effortlessly, eliminating the necessity for training. It could serve as a substitute for measuring tapes. Nonetheless, the study recognizes constraints, such as requiring a defined distance from objects to achieve resolution. Moreover, working with LiDAR may present challenges on extremely dark or highly reflective surfaces. Canvas 3D Pocket is another iOS app used by researchers in crime reconstruction, as in the experiment by [PERSON] et al. [20]. Their results showed an error rate ranging up to 8% compared to the actual benchmark dimensions of their mock-up crime scene. They also stated that their proposed application is a cost-efficient tool for reconstructing crime scenes. However, other factors must be considered when choosing tools, such as case sensitivity and the potential impact of the error, even if the effect on the investigation is small. The study conducted by [PERSON] et al. [21] aimed to enhance crash investigation methods. They utilized data from a LiDAR sensor placed at the center of an automated vehicle. According to their findings, LiDAR proves its capability to detect vehicles better than cameras. The research underlines how analyzing sensor data from autonomous vehiclescan significantly improve crash investigations by considering factors like the reaction times of systems and human drivers. Nonetheless, it also emphasizes the necessity for new protocols to analyze sensor data effectively. This highlights the importance of efforts among companies, law enforcement agencies, and legal systems to develop these protocols. [PERSON] and [PERSON] [5] reviewed existing research on 3D crime scene reconstruction, focusing on the role of LiDAR scanners in generating 3D maps of crime scenes. Their study revealed that LiDAR scanners can scan accurate crime scenes as well as reduce the chance of scene data being contaminated or manipulated. Moreover, portable gadgets such as iPads equipped with LiDAR sensors provide first responders with mobility and flexibility when working on crime scenes. Another work, reviewing the latest 3D tools and methodologies in crime scene reconstruction, was performed by [PERSON] et al. [6]. They conducted a state-of-the-art overview of 3D technology tools and their applications in crime scene reconstruction, including LiDAR technology. According to the study, numerous factors influence the selection of appropriate technology, such as technical requirements, convenience of use, cost, plus scanning time.