1. Course Project Lists for ITCS6157 Jianping Fan

2. Project Implementation Lists Automatic Image Clustering You can download 1,000,000 images from You can extract one of the following visual features: color histogram or SIFT features, you can also try CNN features, you can get source code from http://clickdamage.com/sourcecode/index.php You can apply AP clustering technique to get an optimal partition of these 1,000,000 images according to their visual similarity, you can get AP clustering source code from http://www.image-net.org/ http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm

3. Project Implementation Lists Image Query Result Clustering You can go to Google Images and type in keywords such as ``apple”, ``bank”, ``cloud” et al Download the returned images (more than 1000 images), total images will be 100,000. Extract color histogram or SIFT by using http://clickdamage.com/sourcecode/index.php Apply AP clustering to get an optimal partition of the returned images http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm

4. Project Implementation Lists Automatic Object Detection You can download 1000 images for each of 100 object classes such as``sky”, ``dog”, ``building” from You can extract one of the following visual features: color histogram or SIFT features, you can get source code from http://clickdamage.com/sourcecode/index.php You can apply SVM classifiers to detect these three object classes from 200 test images, you can get SVM classifier training source code from http://www.image-net.org/ http://svmlight.joachims.org/

5. Project Requirements Project implementation: you need to spend time to understand the project and the relevant source code and compile these source codes and make them work in your computer and try to make some revisions. Penalties: TA will test your system by using his images, so it is easy for us to check whether you really do the project or not. If we find that you did not spend enough time to work on your project, you will receive big penalties on your project grade.

6. Group or not Each group may have no more than 3 students We encourage individual project & bonus is expected for individual project Bonus will be given to good implementation such as improving on algorithms or including nice interface & visualization