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

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*Integration of Microsoft Tag into photos
 
*Integration of Microsoft Tag into photos
 
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*Saving learning state to be done in Iteration 7
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*Saving state to be done in Iteration 6
 
*Addition of behavioural parameters for gender recognition
 
*Addition of behavioural parameters for gender recognition
 
*Integration of gender recognition (with behavioural parameters) with photo taking
 
*Integration of gender recognition (with behavioural parameters) with photo taking

Revision as of 22:45, 29 September 2012

Home

Team/Project Partners

Project Overview

Project Management

Design Specifications

Technical Applications


Project Schedule Methodology Schedule & Bug Metrics Gender Recognition Metrics Risk Management Minutes Repository

Post-Acceptance Project Schedule

Planned Schedule Summary

This is the latest schedule amended prior to the beginning of iteration 3. After numerous discussions, we have been informed that CMA would really like to have photo-taking feature. Our primary research of measurement collection in iteration 1 has also shown us that it is not possible to determine gender based on Waist-Hip ratio as waist is not detected by Kinect. The highlight of the schedule amendment is hence the changes of interactive features to photo taking feature and gender recognition based on 4 parameters: height, shoulder length, whether shopper is holding on to a handbag, and whether shopper is wearing long skirt. The focus will be on gender recognition based on neural network until midterm, followed by development of photo taking feature post midterm.


WithPhotoTakingScheduleSummary.png


Access previous planned schedules to view earlier planned schedules prior to firming up of client requirements and primary research on differences between male and female.

Weekly Progress

Week Date Scheduled Features Completed Features Pending Features/Remarks
1 17/08/12 – 24/08/12
  • Explore Classifier Algorithm (CA)
  • Measurement collection
  • Theoretical understanding of Neural Network (NN) and its classification feature
  • Measurement collection
N.A.
2 25/08/12 – 31/08/12
  • Analysis of measurement collection
  • Gender differences trend establishment
  • Gender recognition based on Waist-to-Hip Ratio (WHR)
  • NN classification
  • Analysis of physical measurement collection classification feature
  • Gender differences trend establishment based on physical measurement analysis & secondary research
  • Measurement of height based on image captured by Kinect
  • Found that waist cannot be detected by Kinect, hence dropping WHR
  • Difficulties encountered in implementing NN classification
3 01/09/12 – 08/09/12
  • NN classification & scoring system
  • Parameters expansion: neck & shoulder width
  • Passing of height and shoulder width captured by Kinect to NN
  • NN classification based on height and shoulder width
  • Decided to include parameters hasBag & hasSkirt instead of neck width in the upcoming week
4 09/09/12 – 16/09/12
  • Gender recognition based on complete set of inputs
  • Capturing shopper’s outline
  • Countdown timer
  • Gender recognition based on height, shoulder width, hasBag & hasSkirt
  • Countdown timer
  • Refining of shopper's outline
  • hasSkirt, hasBag parameters to be improved and integrated with passing in of parameters through Kinect
5 17/09/12 – 23/09/12
  • Capturing of photo
  • Backward propagation
  • Saving learning state
  • Integration of photo taking with gender recognition
  • Capturing of photo
  • Backward propagation
  • Integration of photo taking with gender recognition
  • Saving learning state
6 24/09/12 – 29/09/12
  • Microsoft Tag
  • Saving learning state
  • Advertisement Management System page
  • Refining overlaying of augmented background
  • Integration of Microsoft Tag into photos
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking
  • Microsoft Tag
  • Advertisement Management System page
  • Refining overlaying of augmented background
  • Integration of Microsoft Tag into photos
  • Saving state to be done in Iteration 6
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking

Behavioural parameters were not very accurate

7 01/10/12 – 06/10/12
  • Using real figures instead of Kinect figures
  • Addition of behavioural parameters for gender recognition
  • Integration of gender recognition (with behavioural parameters) with photo taking
  • Integration of Microsoft Tag, gender recognition, and photo taking

Midterm Wiki

M.O.O.T Midterm Wiki
1. Project Progress Summary
1.1. Project Highlights
2. Project Management
2.1. Project Status
2.2. Project Schedule
2.3. Project Metrics
2.4. Project Risks
2.5. Technical Complexity
3. Quality of Product
3.1. Intermediate Deliverables
3.2. Deployment
3.3. Testing
4. Reflection
4.1. Team Reflection
4.2. Individual Reflection

Pre-Acceptance

MOOTschedule.jpg