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Difference between revisions of "IS480 Team wiki: 2012T1 M.O.O.T/Project Overview/Learning Outcomes"

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| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | C# programming
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | C# programming
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 +
Programming for Kinect is done in either C# or Visual Basics. We have chosen to code in C#, using Microsoft Visual Studio.
 +
 +
|-
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| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Machine learning
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| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |
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Introduced into the concept of  machine learning by our supervisor, we are taking the plunge: exploring C# neural network, backward propagation, Sigmoid's alpha value, and more to eventually making the machine smarter over time as more gender recognition has been executed
  
 
|-
 
|-
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Microsoft Tag application
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Microsoft Tag application
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 +
We make use of Microsoft Tag to direct shopper to relevant advertisement or promotion, which will also send data to Promotion / Advertisement Management System
  
 
|-
 
|-
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Kinect set up & calibration
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Kinect set up & calibration
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 +
Setting Kinect up to play XboX games is different from setting it up for AlterSense: we have learnt to set the tilting of angle, adjusting the background color, etc
  
 
|-
 
|-
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Gender recognition methods
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Gender recognition methods
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 +
An increasingly popular yet newly ventured area for us - we explore physical differences based on published research, try doing it with the help of Kinect, as well as developing a sensible scoring system to eventually determine shopper's gender
  
 
|-
 
|-
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Human Computer Interaction
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Human Computer Interaction
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |  
 
+
Natural user interface is a novel concept and apparently there are a lot of learning and experiments we have to undergo in order to better understand how to make AlterSense intuitive enough in terms of gestures
|-
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | Color model management: RGB
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |
 
  
 
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| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | 3D programming: x, y, z & depth
 
| style="background: #FFFFFF; padding-bottom: 20px; padding: 5px 10px 0 18px; width: 40%;" valign="top" | 3D programming: x, y, z & depth
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |
 
| style="background: #FFFFFF; padding-bottom: 20px; padding-left: 16px; width: 60%;" |
 +
We have to put ourselves in the Kinect's shoes - every pixel consists of x, y, and z values - to be able to process image, insert image, and many more
  
 
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Revision as of 15:34, 3 September 2012

Home

Team/Project Partners

Project Overview

Project Management

Design Specifications

Technical Applications


Project Description Project Goals Client's Requirements Deliverables Learning Outcomes
Lessons Learnt
S/N Learning Outcomes How We Are Going To Achieve Them
1. Hard skills
C# programming

Programming for Kinect is done in either C# or Visual Basics. We have chosen to code in C#, using Microsoft Visual Studio.

Machine learning

Introduced into the concept of machine learning by our supervisor, we are taking the plunge: exploring C# neural network, backward propagation, Sigmoid's alpha value, and more to eventually making the machine smarter over time as more gender recognition has been executed

Microsoft Tag application

We make use of Microsoft Tag to direct shopper to relevant advertisement or promotion, which will also send data to Promotion / Advertisement Management System

Kinect set up & calibration

Setting Kinect up to play XboX games is different from setting it up for AlterSense: we have learnt to set the tilting of angle, adjusting the background color, etc

Gender recognition methods

An increasingly popular yet newly ventured area for us - we explore physical differences based on published research, try doing it with the help of Kinect, as well as developing a sensible scoring system to eventually determine shopper's gender

Human Computer Interaction

Natural user interface is a novel concept and apparently there are a lot of learning and experiments we have to undergo in order to better understand how to make AlterSense intuitive enough in terms of gestures

3D programming: x, y, z & depth

We have to put ourselves in the Kinect's shoes - every pixel consists of x, y, and z values - to be able to process image, insert image, and many more

2. Soft skills
Idea pitching
Decentralized teamwork
Retail domain knowledge
Stakeholder management
IT-business communication
Corporate presentation skills
Cross-industry idea application