Skip to content

Cross-Domain Image Matching with Deep Feature Maps

Journal: International Journal of Computer Vision
Published: 2019
Primary Author: Bailey Kong
Secondary Authors: James Supancic, Deva Ramana, Charless Fowlkes
Research Area: Footwear

We investigate the problem of automatically determining what type of shoe left an impression found at a crime scene. This recognition problem is made difficult by the variability in types of crime scene evidence (ranging from traces of dust or oil on hard surfaces to impressions made in soil) and the lack of comprehensive databases of shoe outsole tread patterns. We find that mid-level features extracted by pre-trained convolutional neural nets are surprisingly effective descriptors for this specialized domains. However, the choice of similarity measure for matching exemplars to a query image is essential to good performance. For matching multi-channel deep features, we propose the use of multi-channel normalized cross-correlation and analyze its effectiveness. Our proposed metric significantly improves performance in matching crime scene shoeprints to laboratory test impressions. We also show its effectiveness in other cross-domain image retrieval problems: matching facade images to segmentation labels and aerial photos to map images. Finally, we introduce a discriminatively trained variant and fine-tune our system through our proposed metric, obtaining state-of-the-art performance.

Related Resources

Modeling And iNventory of Tread Impression System (MANTIS): The development, deployment and application of an active footwear data collection system

Modeling And iNventory of Tread Impression System (MANTIS): The development, deployment and application of an active footwear data collection system

This CSAFE webinar was held on March 24, 2022. Presenters: Dr. Richard Stone Iowa State University Dr. Susan Vanderplas University of Nebraska, Lincoln Presentation Description: This webinar details the development,…
Footwear Research in CSAFE

Footwear Research in CSAFE

This presentation provided an overview of CSAFE’s footwear research and was presented at IAI in 2021
The effect of image descriptors on the performance of classifiers of footwear outsole image pairs

The effect of image descriptors on the performance of classifiers of footwear outsole image pairs

Shoe prints are commonly found at the scene of a crime and can sometimes help link a suspect to the scene. Because prints tend to be partially observed or smudgy,…