Missing Persons: An Introduction

Morewitz, Stephen J.; Colls, Caroline Sturdy

doi:10.1007/978-3-319-40199-7_1

Cited by 4 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Computer‐assisted reconstruction can be performed using an anatomical approach or mathematical extrapolation of the facial surface. In general, the reconstruction includes five activities, namely (a) point clouds extraction from head CT data, separating the facial and skull surfaces, (b) building a craniofacial model in 3D space, (c) building a facial template, (d) determine the position of landmarks, and finally (e) reconstruct and render the facial surface [13].…”

Section: Related Work On Computer‐aided Craniofacial Reconstructionmentioning

confidence: 99%

“…Second, a deformation technique is needed that can produce a natural facial impression. However, craniofacial reconstruction is ultimately not about accuracy but recognition and subject identification [13].…”

Section: Introductionmentioning

confidence: 99%

“…FIGURE13 Visualization of prediction points taken from the best hundred probabilities for each landmark. The results scattered but clustered close to the target.…”

mentioning

confidence: 99%

See 2 more Smart Citations

3D craniofacial reconstruction framework using elastic surface deformation based on automatic landmark positioning

Suputra

Sensusiati

Artaria

et al. 2023

IET Image Processing

View full text Add to dashboard Cite

Computer‐aided craniofacial reconstruction (CFR) is a process that aims to estimate facial impressions based on skull remains. It mimics the conventional method with a conceptual model‐based framework. The existing problems in CFR are that landmark annotation is expert‐dependent, landmark processing in the 3D domain has volumetric challenges, and a method based on a population's morphological characteristics (templates). A framework with three stages is proposed: Building a craniofacial model, automatic landmark detection, and surface deformation. Machine learning is deployed to draw local surface correlations as landmarks and automatically detects their position. The local surface context is extracted using the Surface Curvature Feature (SCF) as a 3D descriptor. Using a cluster‐based filter, the average distance (to the ground truth) of the top 20 points is 0.0326 units. Cluster‐based filters are better than mass‐radius‐based filters and consistently give better pinpoint accuracy, especially in multi‐cluster cases. Training data consists of 140,000 SCF for ten landmark classes. The third stage, surface deformation, fits the facial template to the cranial based on the corresponding facial‐cranial landmarks. Five experts from the Anthropology department stated that of the reconstruction results, 91.5% could retain the template details and are accepted as the natural shape of the human face.

show abstract

Section: Related Work On Computer‐aided Craniofacial Reconstructionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

3D craniofacial reconstruction framework using elastic surface deformation based on automatic landmark positioning

Suputra

Sensusiati

Artaria

et al. 2023

IET Image Processing

View full text Add to dashboard Cite

show abstract

“…Important information when creating a geographic profile includes when and where the victim was last seen, the victim's last known position, the residences and workplaces of potential suspects (anchor points), locations that the offender and victim frequented, the potential routes taken to and from each point of interest, physical and mental barriers such as highways and rivers, and the activities undertaken by both the offender and the victim on the day of disappearance (Keppel and Weis 1994). This information is typically obtained by the police during the investigation, from as early as the initial missing person's report to interviewing victims, family members/friends, witnesses, and potential suspects (Barone et al 2021;Broadbent et al 2018;Gardner and Krouskup 2018;Keatley 2018;Keppel and Weis 1994;Morewitz and Colls 2016). Other relevant information can include a victim profile, which is not used to identify who the victim is (as this is usually known), but to identify what may have happened to them, based on their known psychological well-being and lifestyle choices (Foy 2016;Keatley 2018).…”

Section: Intelligence Case-specific Informationmentioning

confidence: 99%

More than an Offender Location Tool: Geographic Profiling and Body Deposition Sites

Berezowski

MacGregor

Ellis

et al. 2021

J Police Crim Psych

View full text Add to dashboard Cite

In homicide cases, it is difficult to provide resolution for the bereaved or to obtain a successful criminal conviction of the guilty party when no body is found. Since the mid-nineteenth century, geographic and environmental patterns have been used to better understand the relationship between crime and its environment. Now known as geographic profiling, practitioners in this field amalgamate criminological, psychological, and geographical knowledge, as well as aspects of mathematics, statistics, and physics to identify spatial patterns associated with criminal behaviour as a means of locating anchor points of an offender (where they live, or work). The same techniques can also be used to locate the covert body deposition sites of their victims. This paper aims to (1) provide a brief summary of criminal behaviour and the environment and how understanding their relationship can be helpful to geographic profiling, (2) amalgamate the available literature on the application of geographic profiling in locating clandestine graves (as most documented uses are to locate offender residences), and (3) include a geographic profile of Ivan Milat, an Australian serial killer (officially) active from 1989 to 1992, demonstrating how geographic profiling techniques can help to identify additional victims and potential body deposition sites. The information in this review will be helpful to law enforcement and practitioners to improve missing persons investigations and searches for clandestine graves.

show abstract

“…As Ritter to fall behind in recording these cases and investigating (McMenamin, 2008;Ritter, 2007). The National Crime Information Center, NCIC, is a database used by law enforcement agencies to record information on missing persons and various crimes (McMenamin, 2008;Morewitz & Colls, 2016). However, not all law enforcement agencies are diligent in reporting these cases to the NCIC.…”

Section: Missing Persons Databasesmentioning

confidence: 99%

The sociology of missing women: Evidence from the national missing and unidentified persons system

Beatty¹

View full text Add to dashboard Cite

Missing Persons: An Introduction

Cited by 4 publications

References 4 publications

3D craniofacial reconstruction framework using elastic surface deformation based on automatic landmark positioning

3D craniofacial reconstruction framework using elastic surface deformation based on automatic landmark positioning

More than an Offender Location Tool: Geographic Profiling and Body Deposition Sites

The sociology of missing women: Evidence from the national missing and unidentified persons system

Contact Info

Product

Resources

About