Part 1- Introduction The report contains the...
CSE3/4VIS Visual Information Systems Paper Editing Services
The weight of this assessment is 30% of your overall marks. The assignment aims at consolidating your knowledge base and developing practical skills to build a face recognition system using eigenfaces.
Tasks Description (100 marks in total)
This assignment is composed of the following 5 subtasks. You need to use ONLY selective 10 persons’ face images (including yourself ones) in your assignment. That is, selecting 10 (person)x3 (images from the given training dataset that we provide in LMS)=30 images to form your own training dataset to generate eigenfaces, and the remainders (another two images from the same selected persons) will be used as your own test dataset. Please note that the mentioned training and the test dataset below refer to the training dataset and the test dataset that you generate by yourself, rather than the ones that we provided.
• Resize images stored in the training dataset and the test dataset into 40x30, respectively for generating the eigenfaces and performance evaluation (see Table 1 and 2). Repeat this job with image resized as 80x60. [10 marks]
• Determine K1 and K2 according to the following formulas:
Where λ1……> λ2 are the eigenvalues. Describe how do you generate K1 and K2 eigenfaces from the training datasets. Then, demonstrate the top 10 eigenfaces (corresponding to the top 10 eigenvalues). [20 marks]
• Using 1-NN, 3-NN and 5-NN classifiers to recognize all images for the test datasets; Report the average recognition rate in the following tables: [40 marks]
Using your own 2 face images sized as 40x30 from the testing dataset that you built and the selected value of K1, please list 5 top-ranked faces (based on Euclidean distances) from the training dataset with size as 40x30. So, in total, you will have 10 faces to show. Please provide some analyze the results. [20 marks]
Based on your observations and data analysis on the results given in Table 1-2, please draw some conclusions and make comments on the eigenface technology for face recognition. [10 marks]
1. You have to write a well-written report and show good understandings of the eigenface techniques for face recognition. The developed system creates sensible results. You have examined the performance of the system and drew some conclusions in an interesting and sound way. (100-80 marks)
2. A well-written report. You have produced a working system that produces good results. You have exhibited some initiative in the approach taken and the results are presented clearly. A sound analysis of the results is presented. (79 – 60 words)
3. (59-40 marks) - A reasonable report that demonstrates some understandings of the eigenfaces techniques. The system performs reasonably well and the results are presented reasonably clearly.
4. (39-20 marks) - A report that presents some results of a working system. Demonstrating some basic understandings on face recognition.
5. (19-0 marks) - Either no report submitted or a report that shows little or no understanding.
Challenges that students may face in completing this assignment
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