Forensic Mysteries
time dependent variables
003
003
Federal Bureau of Investigation [FBI]
Police Department
future release
age + weight manipulation
In forensic investigations, accurately predicting how a person's appearance changes over time is crucial, particularly for locating wanted fugitives or missing children. Traditional methods involve forensic artists creating age progressions based on the last known photograph and additional information such as lifestyle, employment, and medical history. However, these manual techniques often lack precision due to the inherent complexity and variability of human aging. The challenge was to leverage machine learning and generative AI to analyze aging factors and produce highly accurate approximations of the aging process, enhancing the precision and reliability of forensic age progressions.
Approach
Using advanced machine learning algorithms, we developed a model capable of simulating time dependent variables such as age and weight progression. The model was trained on our dataset to recognize and predict changes in facial features, skin texture, and body morphology as influenced by various factors.
Solution
By harnessing the power of machine learning and generative AI, we developed an advanced tool for forensic age and weight manipulation. Detectives can now provide last known photograph, sketch and relevant background information, and our AI-driven solution generates highly accurate approximations of the individual's appearance over time.
This technology significantly enhances the precision and reliability of forensic age progressions, aiding law enforcement in locating wanted fugitives and missing children more effectively.