Human Face Reconstruction using Divine Proportions and Gestalt for Occluded Video Face Recovery in Forensic Analysis using Deep Learning
S. Anita1, S. Prema2

1S. Anita, Department of Computer Science, B.M.S. College for Women, Basavangudi, Bangalore (Karnataka), India. 

2Dr. S. Prema, Department of Computer Science, Arulmigu Arthanareeswarar Arts and Science College, Thiruchengodu (Tamil Nadu), India.  

Manuscript received on 30 January 2024 | Revised Manuscript received on 08 February 2024 | Manuscript Accepted on 15 February 2024 | Manuscript published on 28 February 2024 | PP: 1-5 | Volume-11 Issue-2, February 2024 | Retrieval Number: 100.1/ijies.B108911020224 | DOI: 10.35940/ijies.B1089.11020224

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Abstract: Forensic video analysis has been used in diverse kind of high-profile cases, global discrepancies, and conflict zones. It is a three-phase process of scientific examination, comparison, and evaluation of video in legal matters. Human face reconstruction using deep learning for occluded video face recovery to aid in forensic analysis is the main objective of this paper. Forensic facial reconstruction is a combination of both scientific methods and artistic skill. In this paper, we introduce a method to reconstruct human faces occluded due to short noise innight-time video clips. A skull database is created with unique skull models with varying shapes, forms and proportions. Human body mathematical model biometric using golden ratio algorithm is proposed and used to find the occluded face proportions. Closure principle of gestalt theory of visual perception is used to fill in the missing parts of a face design and to create a whole faceimage using gan. The proposed model isfound to have 50% lesserreduced Median error rate and 20% reduced Stdev than PrNet and10% lower Mean error rate than 3Dddfav2.

Keywords: Forensic, Face Reconstruction, Golden Ratio, Gestalt.
Scope of the Article: Industrial, Financial and Scientific Applications of All Kinds