A direct method for stereo correspondence based on singular value decomposition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Automated Processing of Shoeprint Images Based on the Fourier Transform for Use in Forensic Science
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Affine Region Detectors
International Journal of Computer Vision
Shoe-Print Extraction from Latent Images Using CRF
IWCF '08 Proceedings of the 2nd international workshop on Computational Forensics
Automated encoding of footwear patterns for fast indexing
Image and Vision Computing
Numismatic Object Identification Using Fusion of Shape and Local Descriptors
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
Footwear print retrieval system for real crime scene marks
IWCF'10 Proceedings of the 4th international conference on Computational forensics
GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floor
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
| Hi-index | 0.00 |
Identification of the footwear traces from crime scenes is an important yet largely forgotten aspect of forensic intelligence and evidence. We present initial results from a developing automatic footwear classification system. The underlying methodology is based on large numbers of localized features located using MSER feature detectors. These features are transformed into robust SIFT or GLOH descriptors with the ranked correspondence between footwear patterns obtained through the use of constrained spectral correspondence methods. For a reference dataset of 368 different footwear patterns, we obtain a first rank performance of 85% for full impressions and 84% for partial impressions.