First semester of 2018

Class hours: mondays and wednesdays from 5:30pm to 7:30pm*

Room: PA-01 & PA-04 (theoretical classes) and Lab. 3 (practical classes)

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Monitors Eric Gamma Muller

Evaluation

Two written tests:
	40 points - 20 points each
Ten practical tests:
	40 points - 4 points each
A seminar/workshop:
	20 points - slides + presentation (30/45 minutes depending on the number of attending students)

Classical Problems

Face Recognition
Iris Recognition
Fingerprint Recognition
Pedestrian Detection
Detection -- Face (License plate, Vehicle, Eye & Iris)
Iris Segmentation
Face Fiducial Points Detection
Person Action Recognition
First-Person Activity Recognition
Spoofing Detection

Proposed Schedule

##

day

Content

01

02/19

Introduction of the course

02

02/21

Problem 01: Face Recognition (Theoretical) [slides1/slides2]

03

02/26

Problem 01: Face Recognition (Practical) [activity1] - Loading databases & Meanfaces

04

02/28

Problem 01: Face Recognition (Practical) [activity1] - Eigenfaces

05

03/05

Problem 01: Face Recognition (Practical) [activity1] - Classification

06

03/07

Problem 02: Face Recognition (Practical) [activity1] - Evaluation/validation

07

03/12

Problem 02: Iris Recognition (Theoretical) [slides]

08

03/14

Problem 02: Iris Recognition (Practical) [activity2] - Loading databases & extracting pupil region

09

03/19

Problem 02: Iris Recognition (Practical) [activity2] - Extracting iris region and normalization

10

03/21

Problem 02: Iris Recognition (Practical) [activity2] - Iris normalization

11

03/26

Problem 02: Iris Recognition (Practical) [activity2] - Computing features (Wavelet & LBP) for Iris Verification & Identification

12

03/28

Problem 02: Iris Recognition (Practical) [activity2] - Computing metrics (FAR/FRR/EER/ROC Curve & Accuracy) for Iris Verification & Identification

13

04/02

1st written test

14

04/04

Problem 03: Fingerprint Recognition (Theoretical) [slides]

15

04/09

Problem 03: Fingerprint Recognition (Practical) [activity3] - Loading databases & Image enhancement

16

04/11

Problem 03: Fingerprint Recognition (Practical) [activity3] - Orientation Maps & Type Annotation

17

04/16

Problem 03: Fingerprint Recognition (Practical) [activity3] - Region of Interest Detection & Singular Point Detection

18

04/18

Problem 03: Fingerprint Recognition (Practical) [activity3] - Singular Point Detection & Type Classification

19

04/23

Problem 03: Fingerprint Recognition (Practical) [activity3] - Thinning & Minutiae Detection

20

04/25

Problem 03: Fingerprint Recognition (Practical) [activity3] - Minutiae Extraction

--

04/30

(no classroom)

21

05/02

Problem 03: Fingerprint Recognition (Practical) [activity3] - Pattern Matching / Score Computation

22

05/07

Problem 03: Fingerprint Recognition (Practical) [activity3] - Pattern Matching / Score Computation

23

05/09

Problem 04: Pedestrian Detection (Theorectical) [slides1/slides2/slides3]

24

05/14

Problem 04: Pedestrian Detection (Practical) [activity4] - Loading databases & Image Pyramids

25

05/16

Problem 04: Pedestrian Detection (Practical) [activity4] - HOG computation

26

05/21

Problem 04: Pedestrian Detection (Practical) [activity4] - Training SVM

27

05/23

Problem 04: Pedestrian Detection (Practical) [activity4] - Hard negative mining

--

05/28

(no classroom) trucks' strike

--

05/30

(no classroom) trucks' strike

28

06/04

Problem 04: Pedestrian Detection (Practical) [activity4] - Sliding windows

29

06/06

Problem 04: Pedestrian Detection (Practical) [activity4] - Non-maximum suppression

30

06/11

Problem 04: Pedestrian Detection (Practical) [activity4] - curve miss rate vs FPPW

31

06/13

2nd written tests

--

06/15

Presentation of grades for written tests and practical activities

32

06/18

Seminars:	EEG brainwaves - Johanna Elisabeth Rogalsky [slides] Object tracking - Fernando Medeiros Dufour [slides] Typing/Keystroke biometrics/dynamics - Rudolf Eckelberg [slides]

33

06/20

Seminars:	Palm print - Peterson Wagner Kava de Carvalho [slides] Thermal images as source for biometrics - Sergio de Andrade Stemplick [slides]

34

06/25

Seminars:	Hand vascular vein - Beatriz Leandro Bonafini [slides] Person action recognition - Valter Luís Estevam Junior [slides] 3D finger printing - Jonathan Rodrigues Szlactha [slides]

35

06/27

Seminars:	Gesture Recognition - Henrique Augusto Richter [slides] Multimodality - face+voice - Israel Barreto Sant'Anna [slides] Voice as biometrics - Laura Silva Lopes [slides] Face Alignment - Daniel Vitor Ruiz [slides] Handwritten signature - Thiago Jorge Adbo [slides]

--

07/02

Final exam

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

Subjects for Seminars

First-person activity recognition
Person action recognition (selected)
Person re-identification
Object tracking (selected)
Face Alignment
Face Frontalization
Gesture Recognition (selected)
Lip recognition
Gait
High resolution fingerprint (pores & ridges)
3D finger printing (selected)
Fingervein
Thermal images as source for biometrics (selected)
Typing/Keystroke biometrics/dynamics (selected)
Retina recognition
Hand geometry
Palm print (selected)
Handwritten signature (selected)
Hand vascular vein (selected)
Ear as biometrics
Voice as biometrics (selected)
ECG as biometrics
EEG brainwaves (selected)
Multimodality - face+iris
Multimodality - iris+eye
Multimodality - face+fingerprint
Multimodality - iris+fingerprint
Multimodality - face+iris
Multimodality - face+voice (selected)

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
FERNANDO MEDEIROS DUFOUR	69	80	30	100	100	40	90	31	14	75		75	approved	75%	2/19 2/26 2/28 3/14 3/26 4/09 4/23 5/07
JOHANNA ELISABETH ROGALSKY	43	70	23	100	100	75	70	33	16	72		75	approved	90%	3/05 4/09 6/06
LAURA SILVA LOPES	60	55	23	100	100	90	70	35	12	70		70	approved	75%	2/19 2/21 2/26 3/19 3/21 4/16 4/23 5/07
PETERSON WAGNER KAVA DE CARVALHO	100	62	32	100	100	40	45	25	14	72		75	approved	75%	3/21 3/28 4/18 4/23 5/07 5/23 6/04 6/11
RUDOLF COPI ECKELBERG	80	67	29	75	80	35	80	26	20	75		80	approved	78%	3/21 4/09 5/02 5/07 5/23 6/06 6/18
THIAGO JORGE ABDO	80	65	29	100	60	65	80	30	10	69		70	approved	78%	2/19 2/21 2/26 2/28 4/25 5/07 5/23
BEATRIZ LEANDRO BONAFINI (M)	40	79	24	100	100	75	70	33	15	72		75	approved	84%	2/21 4/11 4/16 4/23 4/25
HENRIQUE AUGUSTO RICHTER (M)	75	58	27	100	80	65	80	31	17	75		80	approved	84%	2/19 2/21 3/14 3/26 4/04
ISRAEL BARRETO SANT'ANNA (M)	100	80	36	100	100	100	90	39	16	91		95	approved	81%	3/07 3/28 4/16 5/02 5/16 6/20
JONATHAN RODRIGUES SZLACHTA (M)	90	100	38	100	100	100	25	30	16	84		85	approved	84%	3/14 5/21 6/04 6/06 6/11
VALTER LUÍS ESTEVAM JUNIOR (D)	85	100	37	100	100	100	90	39	20	96		100	approved	90%	5/02 5/16 6/20
DANIEL VITOR RUIZ	95	90	37	100	100	40	50	26	20	83		85	approved	81%	3/07 3/12 4/18 5/07 5/23 6/04
SERGIO DE ANDRADE STEMPLICK	60	75	27	100	100	80	90	36	18	81		85	approved	90%	4/16 4/18 6/18

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

CI396 / INFO7071 - Topics in Computer Vision