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Books > Computing & IT > General theory of computing

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Computer-Graphic Facial Reconstruction (Hardcover) Loot Price: R2,442
Discovery Miles 24 420
Computer-Graphic Facial Reconstruction (Hardcover): John G. Clement, Murray K. Marks

Computer-Graphic Facial Reconstruction (Hardcover)

John G. Clement, Murray K. Marks

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Loot Price R2,442 Discovery Miles 24 420 | Repayment Terms: R229 pm x 12*

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This unique books looks at a cost-efficient, fast and accurate means of facial reconstruction--from segmented, decomposed, or skeletal remains--using computer-graphic and computational means.
Computer-Graphic Facial Reconstruction is designed as a valuable resource for those scientists designing new research projects and protocols, as well as a practical handbook of methods and techniques for medico-legal practitioners who actually identify the faceless victims of crime. It looks at a variety of approaches: artificial intelligence using neural networks, case-based reasoning, Baysian belief systems, along with a variety of imaging methods: radiological, CT, MRI and the use of imaging devices.
The methods described in this book complement, or may even replace, the less-reliable, more traditional means of securing identification by presumptive means, i.e., recognition of clothing, personal effects and clay reconstruction.
- Covers cutting-edge technologies in the context of historical forensic reconstruction methods
- Features stellar authors from around the globe
- Bridges the areas of computer graphics, animation, and forensic anthropology

General

Imprint: Academic Press Inc
Country of origin: United States
Release date: July 2005
First published: April 2005
Authors: John G. Clement • Murray K. Marks
Dimensions: 246 x 189 x 29mm (L x W x T)
Format: Hardcover
Pages: 384
ISBN-13: 978-0-12-473051-9
Categories: Books > Computing & IT > General theory of computing > General
Books > Computing & IT > Applications of computing > General
Books > Social sciences > Sociology, social studies > Crime & criminology > Criminal investigation & detection
LSN: 0-12-473051-5
Barcode: 9780124730519

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