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Project Implementation for ITCS6157/8157

Project Implementation for ITCS6157/8157. Jianping Fan Department of Computer Science University of North Carolina at Charlotte http://www.cs.uncc.edu/~jfan. 1. Build a system for supporting semantic image classification. System Components: a. Image analysis and feature extraction.

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Project Implementation for ITCS6157/8157

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  1. Project Implementation for ITCS6157/8157 Jianping Fan Department of Computer Science University of North Carolina at Charlotte http://www.cs.uncc.edu/~jfan

  2. 1. Build a system for supporting semantic image classification System Components: a. Image analysis and feature extraction (1) Image segmentation using JSEG You can download jseg image segmentation source code from: http://vision.ece.ucsb.edu/segmentation/jseg/ (2) Feature extraction: extract color histogram, color moments, Tamular textures (moments et al.) from each homogeneous regions (3) Region classifier training You can download software from: http://www.cs.cornell.edu/people/tj/svm_light/ http://www.csie.ntu.edu.tw/~cjlin/libsvm/

  3. (4) Region merging After the labels for the homogeneous regions are obtained, the neighboring regions with the same label will be merged as one big region for the relevant salient object (5) Interesting point detection You can download software from: http://vision.ucla.edu/~vedaldi/code/sift/sift.html Detecting the object via SIFT features (6) Object-Based feature extraction Extract color histogram, color moments, textures, and SIFT from salient objects

  4. (7) Concept classifier training positive samples negative samples positive support vectors margin negative support vectors You can download software from: http://www.cs.cornell.edu/people/tj/svm_light/ http://www.csie.ntu.edu.tw/~cjlin/libsvm/

  5. You need to build classifiers for: • Salient Objects • Tree, grass, red flower, yellow flower, sky water, sand, road, car, building • Image Concepts • Garden, beach

  6. 2. Build a system for automatic shot detection from MPEG video clips a. Download MPEG source code from: http://www.ivor.it/cle266/ http://bmrc.berkeley.edu/frame/research/mpeg/ b. Compute frame difference between the neighboring frames according to their color histograms c. Make decision via thresholding

  7. What you need to do? • Implement a demonstration system; • Be ready to interpret some functionalities of your implementations; • Understanding the keys

  8. 3. Read research papers and give presentation in class • Understand the research papers deeply! • Prepare slides for presentation; • Answer questions from professor and students • Schedule will be announced next week! You can pick up one of these three and work on it!

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