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 3-Days Visual Analytics (VA) Workshop by NTU ROSE Lab

 

 

Target Audience:

This workshop is an introductory workshop targeted at managers, end-users, and developers who want to know more about visual analytics.

 

Training Outcome:

By the end of the workshop, participants should have a basic understanding of computer vision and image/video processing, and the common algorithms and approaches used.  Participants will also learn about how machine-learning techniques can be used to develop visual analytics applications.

 

Pre-requisites:

Computer Vision Foundation and Object Search

1.       Undergraduate level mathematics

2.       Basic knowledge on computer vision

3.       Basic knowledge on image/video processing

 

Machine Learning and Deep Learning

1.       Algebraic equation basics (linear equation in slope-intercept form: y = mx + b)

2.       Linear Algebra basics

 

 

Detailed Agenda:

Topic

Agenda 

Day 1:

Computer Vision Foundation and Object Search

1.       Introduction to ROSE Lab 

2.       Foundations of Computer Vision & Pattern Recognition

a.       Visual data acquisition and digitalization

b.       Visual data representation

c.       Visual data understanding

3.       Foundations of Image Processing

a.       Basics of Image Processing

b.       Image Filtering

c.       Image Warping

d.       Image Degradation & Restoration

4.       Visual Object Search

a.       Background

b.       Related work

c.       Our approach ( Randomized Visual Phrases - RVP)

5.       Visual Object Search API Hands-on

a.       API overview

b.       Offline indexing API

c.       Online query API

d.       Hands-on of the front-end system

 

Day 2:

Object Detection & Applications of Visual Analytics

1.       Object Detection

a.       Challenges in Computer Vision

b.       Machine Learning vs Deep Learning

c.       Data Preparation

d.       Model Evaluation

e.       Convolutional Neural Networks

f.        Scale Variation

2.       Data Annotation & Object Detection Hands-on

3.       Visual Attributes (clothing, bags, etc)

a.       Image Segmentation

b.       Semantic Segmentation

c.       Fully Convolutional Networks, DeconvNet, and Dilated Convolutions

d.       Instance Segmentation

    1. Image Segmentation & Color Classification

4.       Cross Camera Human Re-ID and API Hands-on

a.       Introduction to Human Re-ID

b.       Data Preparation

c.       Network Structure

d.       Network Training

e.       Model Evaluation

f.        Two-Fold Re-ID Module

g.       Hands-on Session

 

Day 3:

Action Recognition, Biometrics & Face Analytics

1.       Human Action Recognition

a.       RGB Action Recognition

b.       Skeleton Action Recognition

2.       Overview of Biometrics & Soft Biometrics

a.       Introduction to various biometrics

b.       Introduction to soft biometrics

c.       Introduction to biometric recognition framework

3.       Face Detection, Alignment & Recognition

a.       Face Detection

b.       Face Alignment

c.       Face Recognition

d.       Evaluation Metrics for Face Recognition

4.       Case Studies for Face Recognition

a.       Face recognition at chokepoint

b.       Face recognition in surveillance

5.       Face Analytics API Hands-on

6.       Face Anti-Spoofing

a.       Face Spoofing Attacks

b.       Face Spoofing Detection

c.       Domain Generalization with 3D-CNN

d.       Adversarial Examples in Face Recognition

7.       Discussion & Wrap-up

 

 

 

Cost:

·         The workshop is organised on a per company basis and will be conducted in NTU.

·         The cost is SGD $45,000 + GST per 3 day workshop (for up to 12 students from the same company).

 

Training Schedule:

·         The first course in 2020 is scheduled for 24-26 March 2020.​