Evidential analysis for computer generated animation (CGA)

Hussin, Norriza (2006) Evidential analysis for computer generated animation (CGA). PhD thesis, University of Nottingham.

[img] PDF (Thesis - as examined) - Repository staff only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (7MB)
[img]
Preview
PDF (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (10MB) | Preview

Abstract

The purpose of this thesis is to examine the items of legal evidence from cases, which have utilised Computer-Generated Animation (CGA) technology. In particular, it seeks to determine the degree of reliability and accuracy of CGA based on these items of legal evidence. The research design involved both quasi-experimental processes and pragmatic (sensitivity analyses). This design sought to examine the importance of evidence from a number of case studies and addresses the possible measures to be considered when generating such animations for litigation purposes.

A combination of both stages (quasi-experimental and pragmatic, such as comparing written evidence with spatial evidence) was employed in defining the research questions that will be presented in Chapter 1. The analysis in Chapter 7 will show that:

a. evidence has become knowledge (a source of information) to the animator;

b. the items of legal evidence (knowledge) are usually produced by an expert or a police officer with competency, acquaintance and correct information. These items will be discussed in Chapter 4; and

c. the evidence fulfils the conditions for knowledge to authenticate the credibility of (b) above. This will be discussed in Chapter 4.

i

Furthermore, the research findings that will be clarified in Chapter 8 confirm that each item of legal evidence may be used as information for the animator to generate the CGA. The process of generating an animation may not be possible if a single item of legal evidence is the only source of information for the animator. The findings have been strengthened by the implications of literature from the following three areas - reconstruction of an accident or crime, evidence (both legal and philosophical approaches) and knowledge. These topics are discussed in Chapters 2, 3 and 4.

Consequential to the implications, a sensitivity analysis has been conducted in Chapter 9 to further strengthen the implications indicated in the conclusion part of Chapter 8.

Overall, this research hypothesizes the importance of correct information and evidence from the facts of particular cases as vital in generating an animation. The main objectives are to highlight that:

a. legal evidence is a crucial element in generating an animation;

b. items of legal evidence have been prepared by an authorised police officer or expert.

Apart from the items of evidence classified as written, spatial and visual, eyewitness statements have been analysed based on factors associated with human senses. The eyewitness statements have also been examined based on the types and conditions for knowledge, which are explained in Chapter 4.

ii

The assessment will also be conducted using a different approach based on human senses that will be elucidated in Chapter 5. Similar to other classes of evidence, (written, spatial and visual) the eyewitness must also be present at the collision vicinity or crime scene.

This ultimate aim is to reach a particular level of certainty in determining how reliable and accurate an animation is when it is presented in the courtroom. Although there is no definite level of certainty, the reliability and accuracy can be estimated based on the source of information (items of legal evidence).

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Schofield, Damian
Keywords: computer-generated animation, evidence, theory of knowledge, evidential analysis, expert opinion.
Subjects: T Technology > TR Photography
Faculties/Schools: UK Campuses > Faculty of Science > School of Computer Science
Item ID: 10191
Depositing User: EP, Services
Date Deposited: 30 Aug 2006
Last Modified: 13 Jan 2022 14:48
URI: https://eprints.nottingham.ac.uk/id/eprint/10191

Actions (Archive Staff Only)

Edit View Edit View