Larsen H, Budka M, Bennett MR. Technological innovation in the recovery and analysis of 3D forensic footwear evidence: structure from motion (SfM) photogrammetry. Sci Justice. 2021;61(4):356–68. https://doi.org/10.1016/j.scijus.2021.04.003.

Article  PubMed  Google Scholar 

Gieszl R. City of Phoenix Physical Evidence Manual. 1990.

Geradts Z, Keijzer J. The image-database REBEZO for shoeprints with developments on automatic classification of shoe outsole designs. Forensic Sci Int. 1996;82(1):21–31.

Article  Google Scholar 

Alexander A, Bouridane A, Crookes D. Automatic classification and recognition of shoeprints. image Processing and its Applications, Conference Publication No. 465 0 IEEE. 1999;638–641. https://doi.org/10.1049/cp:19990401

De Chazal P, Flynn J, Reilly RB. Automated processing of shoeprint images based on the Fourier transform for use in forensic science. IEEE Trans Pattern Anal Mach Intell Vol. March 2005;27(3):341–50. https://doi.org/10.1109/TPAMI.2005.48.

Al Garni G, Hamiane M. A novel technique for automatic shoeprint image retrieval. Forensic Sci Int. 2008;181(1–3):10–4. https://doi.org/10.1016/j.forsciint.2008.07.004.

Article  PubMed  Google Scholar 

Nibouche O, Bouridane A, Crookes D, Gueham M, Laadjel M. Rotation invariant matching of partial shoeprints. 2009 13th International Machine Vision and Image Processing Conference. IEEE. https://doi.org/10.1109/IMVIP.2009.24

Dardi F, Cervelli F, Carrato S. A combined approach for footwear retrieval of crime scene shoe marks. Int Conf Imaging Crime Detect Prev (ICDP 2009). 2009;9–9 3. https://doi.org/10.1049/ic.2009.0237.

Wang R, Hong W, Yang N. The research on footprint recognition method based on wavelet and fuzzy neural network. 2009 Ninth International Conference on Hybrid Intelligent Systems. IEEE. 428–432. https://doi.org/10.1109/HIS.2009.300

Francis X, Sharifzadeh H, Newton A, Baghaei N, Varastehpour S. Learning wear patterns on footwear outsoles using convolutional neural networks. 2019 18th IEEE International Conference On Trust, Security and Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science and Engineering (TrustCom/BigDataSE). IEEE. https://doi.org/10.1109/TrustCom/BigDataSE.2019.00067

Patil PM, Kulkarni JV. Rotation and intensity invariant shoeprint matching using Gabor transform with application to forensic science. Pattern Recogn. 2009;42(7):1308–17. https://doi.org/10.1016/j.patcog.2008.11.008.

Article  Google Scholar 

Pei W, Zhu Y, Na Y, He X. Multiscale Gabor wavelet for shoeprint image retrieval. 2009 2nd International Congress on Image and Signal Processing. IEEE https://doi.org/10.1109/CISP.2009.5304124

Parkhi O, Vedaldi A, Zisserman A. Deep face recognition. BMVC 2015-Proceedings of the BMVC. 2015. British Machine Vision Association. https://doi.org/10.5244/C.29.41

Zhang Y, Fu H, Dellandr´ea E, Chen L. Adapting convolutional neural networks on the shoeprint retrieval for forensic use. Biometric Recognition: 12th Chinese Conference, CCBR 2017, Shenzhen, China, October 28–29, 2017, Proceedings 12. Springer International Publishing. https://doi.org/10.1007/978-3-319-69923-3_56

Richetelli N, Lee MC, Lasky CA, Gump ME, Speir JA. Classification of footwear outsole patterns using Fourier transform and local interest points. Forensic Sci Int. 2017;275:102–9. https://doi.org/10.1016/j.forsciint.2017.02.030.

Article  PubMed  Google Scholar 

Kong B, Supancic J, Ramanan D, Fowlkes C. Cross-domain forensic shoeprint matching. Paper presented at the BMVC. London, 2017 Sep.

Kortylewski A, Vetter T. Probabilistic Compositional Active Basis Models for Robust Pattern Recognition. BMVC. 2016 Sep. https://doi.org/10.5244/C.30.30

Ma Z, Ding Y, Wen S, Xie J, Jin Y, Si Z, et al. Shoe-print image retrieval with multi-part weighted CNN. IEEE Access. 2019;7:59728–36. https://doi.org/10.1109/ACCESS.2019.2914455.

Article  Google Scholar 

Hassan M, Wang Y, Pang W, Wang D, Li D, Zhou Y, et al. GUV-Net for high fidelity shoeprint generation. Complex Intell Syst. 2021;1–15. https://doi.org/10.1007/s40747-021-00558-9.

Xin Y, Tang Y, Yang Z. Shoe Print Retrieval Algorithm Based on Improved EfficientnetV2. In: Biometric Recognition: 16th Chinese Conference, CCBR 2022, Beijing, China, November 11–13, 2022. Cham (Switzerland): Springer Nature Switzerland; 2022. pp. 444 – 54. https://doi.org/10.1007/978-3-031-20233-9_45

Li D, Li Y, Liu Y. Shoeprint Image Retrieval based on dual knowledge distillation for Public Security internet of things. IEEE Internet Things J. 2022;9(19):18829–38. https://doi.org/10.1109/JIOT.2022.3162326.

Article  Google Scholar 

Kovalenko A. Fixation and examination of volumetric tracks of footwear using 3D scanning technologies. KNDISE Digest. 2022;67:46. https://doi.org/10.33994/kndise.2022.67.46.

Article  Google Scholar 

UniSvalbard. Geo-SfM. https://unisvalbard.github.io/Geo-SfM/ Accessed 18 Jul 2023.

Szilvśi-Nagy M, Matyasi GY. Analysis of STL files. Math Comput Model. 2003;38(7–9):945–60. https://doi.org/10.1016/S0895-7177(03)90079-3.

Article  Google Scholar 

Qi CR, Su H, Mo K, PointNet. Deep learning on point sets for 3D classification and segmentation. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2017.

Vanderplas S, Elias GB, Kruse J, Carriquiry A, Renfro S. Longitudinal Shoe Study: 3D Shoe Scans. Iowa State University. 2019. https://iastate.figshare.com/articles/dataset/Longitudinal_Shoe_Study_3D_Shoe_Scans/10779986 Accessed 16 Jun 2023.

Keras. Jun. PointNet. https://keras.io/examples/vision/pointnet/ Accessed 16 2023.

Fawcett T. An introduction to ROC analysis. Pattern Recognit Lett. 2006;27(8):861–74. https://doi.org/10.1016/j.patrec.2005.10.010.

Article  Google Scholar 

Powers DM. Evaluation: from precision, recall, and F-measure to ROC, informedness, markedness, and correlation. arXiv preprint arXiv:2010.16061. 2020. https://doi.org/10.48550/arXiv.2010.16061

Chicco D, Jurman G. The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC Genomics. 2020;21(1):1–13. https://doi.org/10.1186/s12864-019-6413-7.

Article  Google Scholar 

Cao C, Liu F, Tan H, Song D, Shu W, Li W, et al. Deep learning and its applications in biomedicine. Genomics Proteom Bioinf. 2018;16(1):17–32. https://doi.org/10.1016/j.gpb.2017.07.003.

Article  Google Scholar 

Google AI. ROC ve AUC. Google Developers, Google, 2023, https://developers.google.com/machine-learning/crash-course/classification/roc-and-auc. Accessed 16 Jun 2023.

Shafique S, Kong B, Kong S, Fowlkes C. Creating a Forensic Database of Shoeprints from Online Shoe-Tread Photos. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2023:858 – 68. https://doi.org/10.1109/WACV56688.2023.00092

Larsen HJ, Bennett MR. Recovery of 3D footwear impressions using a range of different techniques. 2020. J Forensic Sci. 2021;66:1056–64. https://doi.org/10.1111/1556-4029.14662.

Article  PubMed  Google Scholar