Characterizing a Debris Field Using Digital Mosaicking and CAD Model Superimposition from Underwater Video

Vincelli, Jay; Calakli, Fatih; Stone, Michael; Forrester, Graham E.; Jarrell, John D.; Mellon, Timothy

doi:10.14358/pers.82.3.223

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2018

Publication Types

Select...

Article1

Relationship

Self Cite1

Independent0

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In our previous publication on the same subject matter, we detailed our methodology for superimposing CAD models of landing gear on underwater video [10]. In that case study, a man-made rope was visible adjacent to two pieces of purported landing gear.…”

Section: Introductionmentioning

confidence: 99%

Identification of a putative man-made object from an underwater crash site using CAD model superimposition

Vincelli

Calakli

Stone

et al. 2018

Forensic Science International

Self Cite

View full text Add to dashboard Cite

In order to identify an object in video, a comparison with an exemplar object is typically needed. In this paper, we discuss the methodology used to identify an object detected in underwater video that was recorded during an investigation into Amelia Earhart's purported crash site. A computer aided design (CAD) model of the suspected aircraft component was created based on measurements made from orthogonally rectified images of a reference aircraft, and validated against historical photographs of the subject aircraft prior to the crash. The CAD model was then superimposed on the underwater video, and specific features on the object were geometrically compared between the CAD model and the video. This geometrical comparison was used to assess the goodness of fit between the purported object and the object identified in the underwater video.

show abstract

Section: Introductionmentioning

confidence: 99%