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Navigating a Virtual Environment Using Computer Vision

10,000 3,000

Topic Description

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Summary
The project set out to develop a computer vision interface to navigate an existing virtual
environment. In order to do this research first had to be carried out into the various techniques
available for such a task, baring in mind the scope of the project and resources available. The
minimum requirements for the project were met and exceeded, with the development of an
accurate recognition system successfully integrated with ‘The Maze’ virtual environment to
allow successful navigation of the environment. Alongside this, investigations have been
made into methods not used in the final system with conclusions drawn that could aid future
work in this area

Table of contents
1. INTRODUCTION………………………………………………………………………………………………… 1
1.1 Problem description ………………………………………………………………………………………. 1
1.2 Project Scope………………………………………………………………………………………………… 1
1.3 Objectives, Minimum Requirements and Deliverables………………………………………… 1
1.4 Project Schedule……………………………………………………………………………………………. 4
2. BACKGROUND RESEARCH………………………………………………………………………………. 6
2.1 INTRODUCTION …………………………………………………………………………………………………. 6
2.2 POSSIBLE DETECTION APPROACHES……………………………………………………………………… 6
2.2.1 Three-dimensional models……………………………………………………………………………. 7
2.2.2 Two-dimensional models ……………………………………………………………………………… 7
2.2.3 Background subtraction techniques ………………………………………………………………. 8
2.2.4 Hidden Markov Models ……………………………………………………………………………… 10
2.2.5 Temporal models ………………………………………………………………………………………. 11
2.2.5.1 The approach ……………………………………………………………………………………… 11
2.2.5.2 The results …………………………………………………………………………………………. 12
2.3 POSSIBLE RECOGNITION APPROACHES………………………………………………………………… 12
2.3.1 Moments ………………………………………………………………………………………………….. 12
2.3.2 Shape contexts ………………………………………………………………………………………….. 13
2.4 A PREVIOUS APPLICATION………………………………………………………………………………… 13
2.5 CONCLUSIONS…………………………………………………………………………………………………. 14
3. DESIGN……………………………………………………………………………………………………………… 16
3.1 OVERVIEW ……………………………………………………………………………………………………… 16
3.1.1 Choice of language……………………………………………………………………………………. 17
3.2 THE VISION INTERFACE ……………………………………………………………………………………. 17
3.2.1 Motion detection……………………………………………………………………………………….. 17
3.2.2 Action recognition …………………………………………………………………………………….. 19
3.2.2.1 Choosing appropriate actions ……………………………………………………………….. 19
3.2.2.2 Representation of actions …………………………………………………………………….. 23
3.2.2.3 Comparison of actions…………………………………………………………………………. 25
3.3 NAVIGATING THE ENVIRONMENT ………………………………………………………………………. 26
3.3.1 Converting actions to movement …………………………………………………………………. 26
3.4 INTEGRATION………………………………………………………………………………………………….. 27
4. IMPLEMENTATION…………………………………………………………………………………………. 28
4.1 INTRODUCTION ……………………………………………………………………………………………….. 28
4.2 MEI OR MHI? …………………………………………………………………………………………………. 28
4.3 TRAINING WITH ISOLATED ACTIONS…………………………………………………………………… 29
4.4 IMPROVING SPEED……………………………………………………………………………………………. 30
4.5 USING VARIANCE OF ACTION IMAGES ………………………………………………………………… 30
4.6 DYNAMIC ACTION FRAMES ……………………………………………………………………………….. 32
4.7 MHI WITH DYNAMIC ACTION FRAMES?………………………………………………………………. 34
5 EVALUATION……………………………………………………………………………………………………. 36
5.1 ACCURACY OF RECOGNITION SYSTEM………………………………………………………………… 36
5.1.1 Using MEI ……………………………………………………………………………………………….. 36
5.1.1.1 Same person training data ……………………………………………………………………. 36
5.1.1.2 Different person training data……………………………………………………………….. 37
5.1.2 Using MHI……………………………………………………………………………………………….. 39
5.1.2.1 Same person training data ……………………………………………………………………. 39
iv
5.1.2.2 Different person training data……………………………………………………………….. 40
5.1.3 Robustness testing …………………………………………………………………………………….. 41
5.1.3.1 Varying distance from the camera…………………………………………………………. 41
5.1.3.2 Varying lighting conditions………………………………………………………………….. 42
5.2 USER FEEDBACK AND ANALYSIS ……………………………………………………………………….. 43
5.2.1 Accuracy of navigation: 3.5 ……………………………………………………………………….. 43
5.2.2 Responsiveness: 3……………………………………………………………………………………… 44
5.2.3 Ease of use: 3.5…………………………………………………………………………………………. 44
5.2.4 Realism: 4………………………………………………………………………………………………… 44
6 DISCUSSION AND CONCLUSIONS…………………………………………………………………… 45
6.1 VISION……………………………………………………………………………………………………………. 45
6.1.1 Accuracy………………………………………………………………………………………………….. 45
6.1.2 Robustness ……………………………………………………………………………………………….. 46
6.1.3 Extensibility ……………………………………………………………………………………………… 47
6.2 NAVIGATION…………………………………………………………………………………………………… 47
6.2.1 Accuracy………………………………………………………………………………………………….. 47
6.2.2 Responsiveness …………………………………………………………………………………………. 48
6.2.3 Realism ……………………………………………………………………………………………………. 48
6.4 POSSIBLE FUTURE ENHANCEMENTS……………………………………………………………………. 49
6.5 SUMMARY………………………………………………………………………………………………………. 49
REFERENCES………………………………………………………………………………………………………. 51
APPENDIX A: REFLECTION OF WORK …………………………………………………………….. 53
1 TIME MANAGEMENT…………………………………………………………………………………………… 53
1.1 Take your schedule seriously……………………………………………………………………. 53
1.2 Project is a priority ………………………………………………………………………………… 53
1.3 Start early …………………………………………………………………………………………………… 53
2 SEEK HELP ……………………………………………………………………………………………………. 54
3 USE THE DEMONSTRATION ……………………………………………………………………………… 54
4 WRITING THE REPORT…………………………………………………………………………………….. 54
4.1 One step at a time …………………………………………………………………………………… 54
4.2 Look at past projects (but not too much!)…………………………………………………… 55
4.3 Look at the mark scheme …………………………………………………………………………. 55
5 TRY TO ENJOY THE EXPERIENCE………………………………………………………………………. 55
APPENDIX B: PROJECT MANAGEMENT…………………………………………………………… 56
APPENDIX C: USER FEEDBACK FORM

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