Teaching Assistant: Yagmur Cinar
Wednesdays 11h15 - 12h45 in H206
Verify Lecture Locations in ADE
Class notes (pdf)
05 October 2016 Learning and
Evaluation of Pattern Recognition Processes
12 October 2016 Face Detection
using Color Histograms
12 October 2016 Lab Project 1: Face Detection with Color Histograms
of Skin Pixels (Due Wednesday 9 Nov)
12 October 2016 Lab Project 1: Evaluation Criteria and
12 October 2016 UMASS FDDB: Face Detection Data Set and
12 October 2016 Background Reading: [Jain and Learned-Miller 2010],
19 October 2016 Progamming Clinic: Python, OpenCV,
Face Image Data Bases
26 October 2016 Viola Jones
Face Detector - Image Description with Haar like features, Boosted
Learning, Cascade Classifiers.
26 October 2016 Background Reading: [Viola-Jones CVPR 2001]
9 November 2016 Lab Project 1 Project Team Presentations.
9 November 2016 Lab Project
2: Viola Jones Faces Detector (Evaluation Criteria)
December, Written reports due Wednesday 14 December)
16 November 2016 No Class - Lab Project 1 written reports due by email (Lab 1 Evaluation Criteria)
23 November 2016 Eigen Faces - Face
Detection and Recognition with Principal Components Analysis
30 November 2016 NO CLASS - Work on Lab Project 2.
7 December 2016 Viola Jones Face Detector - Project Team
14 December 2016 Lab 2 Viola Jones Face Detector: Written Project
14 December 2016 Artificial Neural Networks: Introduction to
Neural Networks, Regression Analysis and
14 December 2016 Background Reading:
4 January 2017 Artificial Neural Networks: Training Multi-layer networks with Back-Propagation
4 January 2017 Lab Project 3: Face Detection with Artificial
4 January 2017 Paper on Xavier GLORIOT's initialisation procedure
10 January 2017 Make up class for 16 November: Perceptrons, Support
10 January 2017 Background Reading: SVM Face Detection [Osuna et al 1997]
11 January 2017 Convolutional
Neural Networks, Pooling, Auto-Encoders
18 January 2017 Project Team Presentations for Lab 3
18 January 2017 Review of Course, Preparation for Exam.
25 January 2017 Written reports for Lab project 3 due
6-11 February 2017 Exams.
Some Notes on Performance Evaluation:
Performance Evaluation Metrics (supplement to lecture 1).
Face Detection Data Sets:
Below we list of face detection datasets.
FDDB dataset: FDDB dataset contains the annotations for 5,171 faces in a set of 2,845 images.
A face detection benchmark dataset with 32,203 images and labels for
393,703 faces with a high degree of variability in scale, pose and
MALF dataset: Face Detection in the Wild. MALF consists of 5,250 images and 11,931 faces.
AFW dataset: Face Detetion in the Wild. AFW dataset is built using Flickr images. It has 205
images with 473 labeled faces.
For each face, annotations include a
rectangular bounding box, 6 landmarks and the pose angles.
IJB-A dataset: US NIST IJB-A dataset for face detection and face
recognition. IJB-A contains 24,327 images and 49,759 faces.
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condition of including a citation:
Crowley, J. L. , "Class Notes - Pattern Recognition and Machine
Learning", ENSIMAG, Grenoble Institut Polytechnique,
Crée par James L.
Crowley. Last update 3 Jan 2017