2015 |
dos Junior, Cassio Elias Santos Partial Least Squares for Face Hashing Masters Thesis Federal University of Minas Gerais, 2015. Resumo | Links | BibTeX | Tags: DeepEyes, Face Identification, Face Recognition, GigaFrames, Indexing Structure, Local Sensitive Hashing, Partial Least Squares, VER+ @mastersthesis{Santos:2015:MSc, title = {Partial Least Squares for Face Hashing}, author = {Cassio Elias Santos dos Junior}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/dissertation_2015_Cassio.pdf}, year = {2015}, date = {2015-08-24}, school = {Federal University of Minas Gerais}, abstract = {Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature.}, keywords = {DeepEyes, Face Identification, Face Recognition, GigaFrames, Indexing Structure, Local Sensitive Hashing, Partial Least Squares, VER+}, pubstate = {published}, tppubtype = {mastersthesis} } Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature. |
dos Junior, Cassio Elias Santos; Kijak, E; Gravier, G; Schwartz, William Robson Learning to Hash Faces Using Large Feature Vectors Inproceedings Content-Based Multimedia Indexing (CBMI), 13th International Workshop on, pp. 1–6, IEEE, 2015. Links | BibTeX | Tags: Face Identification, Face Recognition, GigaFrames, Indexing Structure, Locality Sensitive Hashing, Partial Least Squares, SmartView, VER+ @inproceedings{santos2015learning, title = {Learning to Hash Faces Using Large Feature Vectors}, author = {Cassio Elias Santos dos Junior and E Kijak and G Gravier and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2015-Learning_to_Hash_Faces_Using_Large_Feature_Vectors.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {Content-Based Multimedia Indexing (CBMI), 13th International Workshop on}, pages = {1--6}, publisher = {IEEE}, keywords = {Face Identification, Face Recognition, GigaFrames, Indexing Structure, Locality Sensitive Hashing, Partial Least Squares, SmartView, VER+}, pubstate = {published}, tppubtype = {inproceedings} } |
2014 |
Dutra, Cristianne Rodrigues Santos; Rocha, M C; Schwartz, William Robson Person Re-Identification Based on Weighted Indexing Structures Inproceedings Iberoamerican Congress on Pattern Recognition (CIARP), pp. 359-366, Springer International Publishing, 2014. Links | BibTeX | Tags: ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, SmartView @inproceedings{Dutra:2014:CIARP, title = {Person Re-Identification Based on Weighted Indexing Structures}, author = {Cristianne Rodrigues Santos Dutra and M C Rocha and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2014_CIARP_Dutra.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {Iberoamerican Congress on Pattern Recognition (CIARP)}, volume = {8827}, pages = {359-366}, publisher = {Springer International Publishing}, series = {Lecture Notes in Computer Science}, keywords = {ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, SmartView}, pubstate = {published}, tppubtype = {inproceedings} } |
2013 |
Dutra, Cristianne Rodrigues Santos; Souza, T; Alves, R; Schwartz, William Robson; Oliveira, L R Re-identifying People based on Indexing Structure and Manifold Appearance Modeling Inproceedings Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 218-225, 2013. Links | BibTeX | Tags: ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, Riemannian Manifold @inproceedings{Dutra:2013:SIBGRAPIb, title = {Re-identifying People based on Indexing Structure and Manifold Appearance Modeling}, author = {Cristianne Rodrigues Santos Dutra and T Souza and R Alves and William Robson Schwartz and L R Oliveira}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/paper_2013_SIBGRAPI.pdf}, year = {2013}, date = {2013-01-01}, booktitle = {Conference on Graphics, Patterns and Images (SIBGRAPI)}, pages = {218-225}, keywords = {ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, Riemannian Manifold}, pubstate = {published}, tppubtype = {inproceedings} } |
2012 |
Schwartz, William Robson; Guo, Huimin; Choi, Jonghyun; Davis, Larry S Face identification using large feature sets Journal Article Image Processing, IEEE Transactions on, 21 (4), pp. 2245–2255, 2012. Links | BibTeX | Tags: Face Identification, Face Recognition, Indexing Structure, Partial Least Squares, PFI @article{schwartz2012face, title = {Face identification using large feature sets}, author = {William Robson Schwartz and Huimin Guo and Jonghyun Choi and Larry S Davis}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2012-Face-identification-using-large-feature-sets.pdf}, year = {2012}, date = {2012-01-01}, journal = {Image Processing, IEEE Transactions on}, volume = {21}, number = {4}, pages = {2245--2255}, publisher = {IEEE url = https://googledrive.com/host/0B53xd8WZN11YeTRvemlqYkJNd0E/paper_2011_TIP.pdf}, keywords = {Face Identification, Face Recognition, Indexing Structure, Partial Least Squares, PFI}, pubstate = {published}, tppubtype = {article} } |
2015 |
Cassio Elias Santos dos Junior Partial Least Squares for Face Hashing Masters Thesis Federal University of Minas Gerais, 2015. Resumo | Links | BibTeX | Tags: DeepEyes, Face Identification, Face Recognition, GigaFrames, Indexing Structure, Local Sensitive Hashing, Partial Least Squares, VER+ @mastersthesis{Santos:2015:MSc, title = {Partial Least Squares for Face Hashing}, author = {Cassio Elias Santos dos Junior}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/dissertation_2015_Cassio.pdf}, year = {2015}, date = {2015-08-24}, school = {Federal University of Minas Gerais}, abstract = {Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature.}, keywords = {DeepEyes, Face Identification, Face Recognition, GigaFrames, Indexing Structure, Local Sensitive Hashing, Partial Least Squares, VER+}, pubstate = {published}, tppubtype = {mastersthesis} } Face identification is an important research topic due to areas such as its application to surveillance, forensics and human-computer interaction. In the past few years, a myriad of methods for face identification has been proposed in the literature, with just a few among them focusing on scalability. In this work, we propose a simple but efficient approach for scalable face identification based on partial least squares (PLS) and random independent hash functions inspired by locality-sensitive hashing (LSH), resulting in the PLS for hashing (PLSH) approach. The original PLSH approach is further extended using feature selection to reduce the computational cost to evaluate the PLS-based hash functions, resulting in the state-of-the-art extended PLSH approach (ePLSH). The proposed approach is evaluated in the dataset FERET and in the dataset FRGCv1. The results show significant reduction in the number of subjects evaluated in the face identification (reduced to 0.3% of the gallery), providing averaged speedups up to 233 times compared to evaluating all subjects in the face gallery and 58 times compared to previous works in the literature. |
Cassio Elias Santos dos Junior; E Kijak; G Gravier; William Robson Schwartz Learning to Hash Faces Using Large Feature Vectors Inproceedings Content-Based Multimedia Indexing (CBMI), 13th International Workshop on, pp. 1–6, IEEE, 2015. Links | BibTeX | Tags: Face Identification, Face Recognition, GigaFrames, Indexing Structure, Locality Sensitive Hashing, Partial Least Squares, SmartView, VER+ @inproceedings{santos2015learning, title = {Learning to Hash Faces Using Large Feature Vectors}, author = {Cassio Elias Santos dos Junior and E Kijak and G Gravier and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2015-Learning_to_Hash_Faces_Using_Large_Feature_Vectors.pdf}, year = {2015}, date = {2015-01-01}, booktitle = {Content-Based Multimedia Indexing (CBMI), 13th International Workshop on}, pages = {1--6}, publisher = {IEEE}, keywords = {Face Identification, Face Recognition, GigaFrames, Indexing Structure, Locality Sensitive Hashing, Partial Least Squares, SmartView, VER+}, pubstate = {published}, tppubtype = {inproceedings} } |
2014 |
Cristianne Rodrigues Santos Dutra; M C Rocha; William Robson Schwartz Person Re-Identification Based on Weighted Indexing Structures Inproceedings Iberoamerican Congress on Pattern Recognition (CIARP), pp. 359-366, Springer International Publishing, 2014. Links | BibTeX | Tags: ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, SmartView @inproceedings{Dutra:2014:CIARP, title = {Person Re-Identification Based on Weighted Indexing Structures}, author = {Cristianne Rodrigues Santos Dutra and M C Rocha and William Robson Schwartz}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/paper_2014_CIARP_Dutra.pdf}, year = {2014}, date = {2014-01-01}, booktitle = {Iberoamerican Congress on Pattern Recognition (CIARP)}, volume = {8827}, pages = {359-366}, publisher = {Springer International Publishing}, series = {Lecture Notes in Computer Science}, keywords = {ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, SmartView}, pubstate = {published}, tppubtype = {inproceedings} } |
2013 |
Cristianne Rodrigues Santos Dutra; T Souza; R Alves; William Robson Schwartz; L R Oliveira Re-identifying People based on Indexing Structure and Manifold Appearance Modeling Inproceedings Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 218-225, 2013. Links | BibTeX | Tags: ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, Riemannian Manifold @inproceedings{Dutra:2013:SIBGRAPIb, title = {Re-identifying People based on Indexing Structure and Manifold Appearance Modeling}, author = {Cristianne Rodrigues Santos Dutra and T Souza and R Alves and William Robson Schwartz and L R Oliveira}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/03/paper_2013_SIBGRAPI.pdf}, year = {2013}, date = {2013-01-01}, booktitle = {Conference on Graphics, Patterns and Images (SIBGRAPI)}, pages = {218-225}, keywords = {ARDOP, Indexing Structure, Inverted Lists, Person Re-Identification, Riemannian Manifold}, pubstate = {published}, tppubtype = {inproceedings} } |
2012 |
William Robson Schwartz; Huimin Guo; Jonghyun Choi; Larry S Davis Face identification using large feature sets Journal Article Image Processing, IEEE Transactions on, 21 (4), pp. 2245–2255, 2012. Links | BibTeX | Tags: Face Identification, Face Recognition, Indexing Structure, Partial Least Squares, PFI @article{schwartz2012face, title = {Face identification using large feature sets}, author = {William Robson Schwartz and Huimin Guo and Jonghyun Choi and Larry S Davis}, url = {http://smartsenselab.dcc.ufmg.br/wp-content/uploads/2019/02/2012-Face-identification-using-large-feature-sets.pdf}, year = {2012}, date = {2012-01-01}, journal = {Image Processing, IEEE Transactions on}, volume = {21}, number = {4}, pages = {2245--2255}, publisher = {IEEE url = https://googledrive.com/host/0B53xd8WZN11YeTRvemlqYkJNd0E/paper_2011_TIP.pdf}, keywords = {Face Identification, Face Recognition, Indexing Structure, Partial Least Squares, PFI}, pubstate = {published}, tppubtype = {article} } |