First semester of 2019

Professor: David Menotti

Class hours: mondays and wednesdays from 7:30pm to 9:30pm*

Room: PC-05 (theoretical classes) and Lab. 5 (practical classes)

email list: https://listas.inf.ufpr.br/cgi-bin/mailman/listinfo/ci1028-menotti

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Evaluation

Two written tests:
	40 points - 20 points each
Four practical tests:
	40 points - where each test is weighted by the number of classes taken
A seminar/workshop:
	20 points - slides + presentation (30/45 minutes depending on the number of attending students)

Classical Problems

1. Face Recognition
2. Iris Recognition
3. Fingerprint Recognition
4. Pedestrian Detection

Proposed Schedule

##	day	Content
01	02/18	Introduction of the course
02	02/20	Problem 01: Face Recognition (Theoretical) [slides1/slides2]
03	02/25	Problem 01: Face Recognition (Practical) [activity1] - Loading databases & Meanfaces
04	02/27	Problem 01: Face Recognition (Practical) [activity1] - Eigenfaces
05	03/04	no classroom -- Carnaval
06	03/06	no classroom -- Carnaval
07	03/11	Problem 01: Face Recognition (Practical) [activity1] - Classification
08	03/13	Problem 02: Face Recognition (Practical) [activity1] - Evaluation/validation
09	03/18	Problem 02: Iris Recognition (Theoretical) [slides]
10	03/20	Problem 02: Iris Recognition (Practical) [activity2] - Loading databases & extracting pupil region
11	03/25	Problem 02: Iris Recognition (Practical) [activity2] - Extracting iris region and normalization
12	03/27	Problem 02: Iris Recognition (Practical) [activity2] - Iris normalization
13	04/01	Problem 02: Iris Recognition (Practical) [activity2] - Computing features (Wavelet & LBP) for Iris Verification & Identification
14	04/03	Problem 02: Iris Recognition (Practical) [activity2] - Computing metrics (FAR/FRR/EER/ROC Curve & Accuracy) for Iris Verification & Identification
15	04/08	1st written test
--	04/10	noshow
16	04/15	Problem 03: Fingerprint Recognition (Theoretical) [slides]
17	04/17	Problem 03: Fingerprint Recognition (Practical) [activity3] - Loading databases & Image enhancement
18	04/22	Problem 03: Fingerprint Recognition (Practical) [activity3] - Orientation Maps & Type Annotation
19	04/24	Problem 03: Fingerprint Recognition (Practical) [activity3] - Region of Interest Detection & Singular Point Detection
20	04/29	Problem 03: Fingerprint Recognition (Practical) [activity3] - Singular Point Detection & Type Classification
--	05/01	(no classroom) holyday
21	05/06	Problem 03: Fingerprint Recognition (Practical) [activity3] - Thinning & Minutiae Detection
22	05/08	Problem 03: Fingerprint Recognition (Practical) [activity3] - Minutiae Extraction
23	05/10*	Problem 03: Fingerprint Recognition (Practical) [activity3] - Pattern Matching / Score Computation
24	05/13	Problem 03: Fingerprint Recognition (Practical) [activity3] - Pattern Matching / Score Computation
--	05/15	no classroom
25	05/20	Problem 04: Pedestrian Detection (Theorectical) [slides1/slides2/slides3]
27	05/22	Problem 04: Pedestrian Detection (Practical) [activity4] - Loading databases & Image Pyramids
28	05/27	Problem 04: Pedestrian Detection (Practical) [activity4] - HOG computation
29	05/27*	Problem 04: Pedestrian Detection (Practical) [activity4] - Training SVM
30	05/29	Problem 04: Pedestrian Detection (Practical) [activity4] - Hard negative mining
31	06/03	Problem 04: Pedestrian Detection (Practical) [activity4] - Sliding windows
31	06/03*	Problem 04: Pedestrian Detection (Practical) [activity4] - Non-maximum suppression
32	06/05	Problem 04: Pedestrian Detection (Practical) [activity4] - curve miss rate vs FPPW
33	06/10	2nd written tests
34	06/12	Seminars: Gait as biometrics - Hamer Iboshi ECG as biometrics - Mariana Carmin First-person activity recognition - Leonardo Joji Takii
35	06/17	Seminars: Voice as biometrics - Glenda Proença Train Typing/Keystroke biometrics/dynamics - Bruno Serbena Multimodality - face+iris - Gabriela Yukari Kimura
35	06/19	Seminars: 3D finger printing - André Starosta Handwritten signature - Diego Roessle Object tracking - Gabriel Alcides Carraro
36	06/24	Seminars: Ear as biometrics - Rayson Laroca Fingervein - Gabriel Salomon Cattle Muzzle Recognition - Wyverson Bonasoli
37	06/26	Seminars: EEG brainwaves - Augusto Lopez Dantas Thermal images as source for biometrics - Bruno Meyer
--	07/01	Final exam (only for undergraduate students)

Support material

• Nothing <???.pdf>

References

• Face Verification

  • Eigenfaces for Recognition, M. Turk and A.Pentland, Journal of cognitive Neuroscience, 1991, vol. 3, no. 1, pages 71-86 -- 14,985 citations on scholar.google.com on 2016/08/03.
  • Eigenfaces vs. Fisherfaces: recognition using class specific linear projection, P. N. Belhumeur, J. P. Hespanha and D. J. Kriegman, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, vol. 19, no. 7, pages 711-720 -- 10,909 citations on scholar.google.com on 2016/08/03.

• Iris Recognition

  • How Iris Recognition Works, J. Daugman, IEEE Transactions on Circuits and Systems for Video Technology, 2004, vol. 14, no. 1, pages 21-30 -- 3,242 citations on scholar.google.com on 2016/08/22.
  • Iris Recognition: An Emerging Biometric Technology, R. P. Wildes, IEEE Proceedings of IEEE, 1997, vol. 85, no. 9, pages 1348-1363 -- 2,334 citations on scholar.google.com on 2016/08/22
  • Toward Noncooperative Iris Recognition: A classification Approach Using Multiple Signatures, H. Proenca and L. A. Alexandre, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007, vol. 29, no. 4, pages 607-612 -- 191 citations on scholar.google.com on 2016/08/22

• Fingerprint Recognition

  • On-line fingerprint verification, A. Jain, L. Hong, R. Bolle, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, vol. 19, no. 4, pages 302-314 -- 1,778 citations on scholar.google.com on 2016/09/19
  • Fingerprint recognition using wavelet features, M. Tico, E. Immonen, P. Ramo, P. Kuosmanen and J. Saarinen, IEEE International Symposium on Circuits and Systems, 2001, vol. 2, pages 21-24 -- 98 citations on scholar.google.com on 2016/09/19
  • Implementation of an automatic fingerprint identification system, P. Huang, C.-Y. Chang and C.-C. Chen, IEEE International Conference on Electro/Information Technology, 2007, pages 461-464 -- 4 citations on scholar.google.com on 2016/09/19
  • Classificaiton of Fingerprint Images, L. Hong and A. Jain, Scandinaval Conference on Image Analysis, 1999, vol. 2, pages 1-7 -- 164 citations on scholar.google.com on 2016/09/19

• Pedestrian Detection

  • Histograms of Oriented Gradients for Human Detection, N. Dalal and B. Triggs, IEEE Conference on Computer Vision and Pattern Recognition, 2005, pages 1-8 -- 15,999 citations on scholar.google.com on 2016/10/17
  • Finding People in Images and Videos, N. Dalal, PhD Thesis, INRIA Rhône-Alpes / Institut National Polytechnique de Grenoble, 2006, 135 pages -- 353 citations on scholar.google.com on 2016/10/19
  • Fast Human Detection Using a Cascade of Histograms of Oriented Gradients, Q. Zhu, S. Avidan, M-C. Yeh and K-T. Cheng, IEEE Conference on Computer Vision and Pattern Recognition, 2006, 1-8, -- 1,365 citations on scholar.google.com on 2016/10/17

Databases

• Face Verification

  • Harvard Robotics Laboratory --
  • ORL (AT&T) -- 10 subjects x 40 images, each one with 92x112 pixels and 256 grey levels
  • The Yale Face Database -- 15 subjects x 11 images, each one with 320 x 243 pixels
  • The Yale Face Database B -- 10 subjects x 576 viewing conditions (9 poses x 64 illuminations) -- 5760+90=5850 images
  • The Extended Yale Face Database B -- 28 humans under 9 poses and 64 illumination conditions (adding 18 subjects)
  • PubFig83 -- 83 subjects x 100 images, each with 100x100 pixels

• Face Expression Recognition

  • The Yale Face Database -- 15 subjects x 11 images, each one with 320 x 243 pixels

• Iris Recognition

  • Chinese Academy of Sciences Institue of Automation (CASIA) --

    • CASIA-IrisV4 Interval
    • CASIA-IrisV4 Lamp

  • University Beira Interior -- Noisy Visible Wavelength Iris (UBIRIS)

    • UBIRIS.v2

• Fingerprint Recognition

  • Fingerprint Verification Competition (FVC2000)

  • Fingerprint Verification Competition (FVC2002)

  • Fingerprint Verification Competition (FVC2004)

  • Fingerprint Verification Competition (FVC2006)

  • PRIP Lab - National Tsing Hua University, Taiwan Prof. C. Chen

    • Lindex101 -- 101 subjects x 4 images (300x300 pixels) -- missing images? try here!
    • Rindex28 -- 28 subjects x 4 images (300x300 pixels)

• Pedestrian Detection

  • MIT (CBCL PEDESTRIAN DATABASE #1) -- 924 images (10/22 Mb) with 64 x 128 PPM format images for training

  • INRIA Person dataset (970Mb)

    • 1208/566 positive windows (train/test) -- 64 x 128 bounding box size with 16/3 border pixels (train/test)
    • 1218/453 negatives images (train/test) -- 2592 x 1944 pixels

  • Caltech Pedestrian Detection Benchmark (6Gb/5Gb)

  • ETH dataset

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Presence in Classes

name	wt.1	wt.2	#wt#	pa.1	pa.2	pa.3	pa.4	#pa#	#sem#	mean	final	mean*	situation	frequency	absences
ANDRÉ FELIPE ALVES STAROSTA	87	65	30	80	80	40	75	26	17	73		75	aprovado	93%	4/17 5/08
BRUNO FREITAS SERBENA	100	99	40	100	100	90	90	37	19	96		100	aprovado	96%	2/25
DIEGO GRACIANO ROESSLE	60	35	19	0	70	70	0	15	0	34		35	reprovado	77%	2/18 2/20 2/25 3/11 3/13 3/18 3/25
GABRIEL ALCIDES CARRARO	40	67	21	0	50	55	60	19	19	59		60	aprovado	77%	2/18 2/20 2/25 3/11 3/20 3/27 4/03
GABRIELA YUKARI KIMURA	85	87	34	100	100	80	80	35	16	85		90	aprovado	90%	4/22 4/24 5/06
GLENDA PROENCA TRAIN	70	50	24	100	90	95	25	29	18	71		75	aprovado	93%	5/06 6/05
GUILHERME SCARIOT RAMOS												0	abandono	22%	2/18 2/20 2/25 2/27 3/20 4/08 4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
HAMER IBOSHI	70	50	24	50	70	45	0	15	18	57		60	aprovado	90%	3/27 4/24 4/29
JONAS SILVEIRA DA COSTA												0	abandono	0%	2/18 2/20 2/25 2/27 3/11 3/13 3/18 3/20 3/25 3/27 4/01 4/03 4/08 4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
LEONARDO JOJI TAKII	85	91	35	100	0	75	50	22	17	75		80	aprovado	96%	5/08
MARIANA CARMIN	67	60	25	50	80	75	60	27	15	67		70	aprovado	90%	2/27 4/22 5/06
MATHEUS DONIZETE MATOS DA SILVA												0	abandono	6%	2/25 2/27 3/11 3/13 3/18 3/20 3/25 3/27 4/01 4/03 4/08 4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
VINICIUS GEOVANE GARCIA												0	abandono	19%	2/18 2/20 2/25 3/27 4/01 4/03 4/08 4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
WILLIAN MARCEL MOSSON												0	abandono	16%	2/18 2/20 2/25 3/11 3/13 3/20 3/25 3/27 4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
ANDERSON TADASHI SANTOS IGARASHI	75	55	26	100	95	95	90	38	19	83		85	aprovado	100%
AUGUSTO LOPES DANTAS	98	60	32	100	100	75	0	24	13	69		70	aprovado	80%	4/22 4/29 5/22 5/27 5/29 6/05
BRUNO HENRIQUE MEYER	98	60	32	100	100	90	90	37	20	89		90	aprovado	96%	6/03
GABRIEL SALOMON ANICETO	100	97	39	100	100	80	95	37	19	95		100	aprovado	90%	2/27 4/22 6/05
RAYSON BARTOSKI LAROCA DOS SANTOS	92	85	35	100	100	95	100	39	20	95		100	aprovado	77%	4/17 5/13 5/22 5/27 5/29 6/03 6/05
RODRIGO LAMPIER DOS SANTOS	25	0	5	50	90			10	0	15		15	abandono	41%	4/15 4/17 4/22 4/24 4/29 5/06 5/08 5/10* 5/13 5/20 5/22 5/27 5/27* 5/29 6/03 6/03* 6/05 6/10
WYVERSON BONASOLI DE OLIVEIRA	90	97	37	100	100	95	95	39	20	96		100	aprovado	93%	5/08 5/22
wt.1 - written test 1 (100 pts)
wt.2 - written test 2 (100 pts)
#wt# - written tests total points in 40%
pa.1 - practical activity 1 (100 pts)
pa.2 - practical activity 2 (100 pts)
pa.3 - practical activity 3 (100 pts)
pa.4 - practical activity 4 (100 pts)
#pa# - practical activites total points in 40%
#sem# - seminars total points in 20%
mean & mean* - final grad

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