Name
Title | ||
|---|---|---|
A cooperative coevolutionary approach dealing with the skull–face overlay uncertainty in forensic identification by craniofacial superimposition |
Abstract | ||
|---|---|---|
Craniofacial superimposition is a forensic process where photographs or video shots of a missing person are compared with the skull that is found. By projecting both photographs on top of each other (or, even better, matching a scanned three-dimensional skull model against the face photo/video shot), the forensic anthropologist can try to establish whether that is the same person. The whole process is influenced by inherent uncertainty mainly because two objects of different nature (a skull and a face) are involved. In previous work, we categorized the different sources of uncertainty and introduced the use of imprecise landmarks to tackle most of them. In this paper, we propose a novel approach, a cooperative coevolutionary algorithm, to deal with the use of imprecise cephalometric landmarks in the skull–face overlay process, the main task in craniofacial superimposition. Following this approach we are able to look for both the best projection parameters and the best landmark locations at the same time. Coevolutionary skull–face overlay results are compared with our previous fuzzy-evolutionary automatic method. Six skull–face overlay problem instances corresponding to three real-world cases solved by the Physical Anthropology Lab at the University of Granada (Spain) are considered. Promising results have been achieved, dramatically reducing the run time while improving the accuracy and robustness. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s00500-011-0770-8 | Soft Comput. |
Keywords | Field | DocType |
face overlay process,cooperative coevolutionary approach,scanned three-dimensional skull model,forensic process,face overlay uncertainty,coevolutionary skull,forensic identification,craniofacial superimposition,face overlay problem instance,face overlay result,face photo,video shot,whole process | Computer vision,Superimposition,Evolutionary algorithm,Computer science,Forensic identification,Robustness (computer science),Forensic anthropology,Artificial intelligence,Overlay,Landmark,Genetic fuzzy systems | Journal |
Volume | Issue | ISSN |
16 | 5 | 1433-7479 |
Citations | PageRank | References |
9 | 0.56 | 16 |
Authors | ||
3 | ||