This webinar is on-demand and available immediately.

The forensic analysis of impression evidence, such as fingerprints or shoeprints, plays a critical role in crime investigation. A common characteristic of impression evidence is that the pattern of interest is often latently hidden in structured clutter and severely occluded. This poses a major challenge to fully automated approaches for impression analysis. This talk discusses a generative approach that integrates the segmentation and classification of latent impressions in a common optimization framework.

Presenter: Adam Kortylewski

Recorded: 02/10/2017