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Recognition of children on age-different images: Facial morphology and age-stable features
Zuzana Caplova1, Valentina Compassi1, Silvio Giancola2
1Università degli Studi di Milano, Dipartimento di Scienze Biomediche per la Salute, Via Mangiagalli 31, 20133 Milano, Italy.
Insights
Facial features change as children grow, complicating identification. However, moles remain stable over time and can aid in recognizing missing children through facial recognition technology.
Area of Science:
- Forensic Science
- Anthropology
- Computer Science
Background:
- Missing children identification is a global challenge, often hindered by changing facial morphology over time.
- Surveillance systems offer potential image data for comparison, but facial changes complicate identification.
Purpose of the Study:
- To determine if facial features remain stable over time for facial recognition.
- To evaluate the utility of moles as age-stable features for child identification.
Main Methods:
- Morphological classification of facial features using an Anthropological Atlas.
- Development of a MATLAB algorithm to assess moles as age-stable recognition features.
Main Results:
- High observer mismatch percentages were found when classifying facial features using atlases.
- Features describing shape showed lower mismatch rates than those describing size.
- The nose tip cleft and chin dimple demonstrated the best observer agreement for categorization and stability.
- Using mole positions as reference points proved objective and useful for recognition.
Conclusions:
- Moles are age-stable facial features valuable for preliminary recognition of missing children.
- Facial recognition methods incorporating mole analysis can enhance identification efforts.
Abstract:
The situation of missing children is one of the most emotional social issues worldwide. The search for and identification of missing children is often hampered, among others, by the fact that the facial morphology of long-term missing children changes as they grow. Nowadays, the wide coverage by surveillance systems potentially provides image material for comparisons with images of missing children that may facilitate identification. The aim of study was to identify whether facial features are stable in time and can be utilized for facial recognition by comparing facial images of children at different ages as well as to test the possible use of moles in recognition. The study was divided into two phases (1) morphological classification of facial features using an Anthropological Atlas; (2) algorithm developed in MATLAB® R2014b for assessing the use of moles as age-stable features. The assessment of facial features by Anthropological Atlases showed high mismatch percentages among observers. On average, the mismatch percentages were lower for features describing shape than for those describing size. The nose tip cleft and the chin dimple showed the best agreement between observers regarding both categorization and stability over time. Using the position of moles as a reference point for recognition of the same person on age-different images seems to be a useful method in terms of objectivity and it can be concluded that moles represent age-stable facial features that may be considered for preliminary recognition.
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