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CS6350: Computer Vision | |
January - May, 2015 |
| Textbooks |
| Richard Szeliski, Computer Vision: Algorithms and Applications, Springer-Verlag London Limited 2011. |
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Computer Vision: A Modern Approach, D. A. Forsyth, J. Ponce, Pearson Education, 2003. |
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| References |
| Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision, Second Edition, Cambridge University Press, March 2004. |
| K. Fukunaga; Introduction to Statistical Pattern Recognition, Second Edition, Academic Press, Morgan Kaufmann, 1990. |
| R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison- Wesley, 1992. |
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| Journals |
| IEEE-T-PAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence). |
| IJCV (International Journal of Computer Vision) - Springer. |
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Topic-Wise References
| 1 | Introduction |
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| 2 | Neighborhood and Connectivity of pixels |
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| 3 | 3D transformations and projection |
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| 4 | Fourier Theory and Filtering in spatial and spectral domains |
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| 5 | Enhancement |
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| 6 | Histogram based image processing |
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| 7 | Concepts in Edge Detection |
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| 8 | Hough Transform |
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| 9 | Image segmentation |
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| 10 | Texture analysis using Gabor filters |
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| 11 | SCALE-SPACE - Theory and Applications |
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| 12 | Local Feature Detectors and Descriptors |
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| 13 | Motion |
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| 14 | Motion Detection and Tracking |
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| 15 | Shape from Shading |
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| 16 | Pattern Recognition |
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| 17 | Wavelet transform |
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| 18 | Morphology |
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Tracking Videos
| Term Project Assignment List | ||||||||
| SL No. | Problem Statement | Performance based marks (indicative) |
Group IDs Alloted (by preference, FCFS) |
Details | ||||
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Preference No. |
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| Satisfactory | Good | Excellent | I | II | III | |||
| 1 | Use of spatio-temporal features for matching (unconstrained) video shots. | 20 | 30 | 36 | -- | -- | -- |
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| 2 | Motion compensation based automatic tracking of object silhouette, under camera movement | 22 | 32 | 41 | -- | -- | -- |
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| 3 | Inane video analysis: classification, Similarity measure | 20 | 35 | 42 | -- | -- | -- |
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| 4 | Face Recognition from LFW, in presence of occlusion and pose | 25 | 36 | 41 | -- | -- | -- |
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| 5 | Towards Expression invariant Face Recognition | 25 | 35 | 42 | -- | -- | -- |
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| 6 | Image based rendering for novel views (equivalent to photosynth) using 3 or more images | 18 | 26 | 36 | -- | -- | -- |
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| 7 | Image enhancement using Super-resolution techniques on low-resolution images | 18 | 28 | 36 | -- | -- | -- |
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Saliency detection from images of multiple objects: Top-down/ bottom-up or combination | 20 | 30 | 38 |
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| 9 | Salient object detection: a discriminative regional feature integration approach | 25 | 35 | 42 | -- | -- | -- |
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| 10 | Domain Adaptation Using Kernel (or manifold alignment) Alignment for Object Categorization | 25 | 32 | 41 | -- | -- | -- |
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| 11 | Semi-supervised clustering for organizing large image/video datasets | 25 | 32 | 41 | -- | -- | -- |
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| 12 | 3-D jigsaw puzzle solving for structure reconstruction from assorted parts | 30 | 35 | 40 | -- |
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| 13 | Discriminative Subspace Clustering | 20 | 30 | 39 | -- | -- | -- |
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| 14 | Comparative Study of the Performances of very recent Feature Extractors, used for Detection, Matching and Recognition | 25 | 35 | 42 | -- | -- | -- |
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| 15 | Multi-Band Texture Segmentation | 30 | 35 | 40 | -- | -- | -- |
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| 16 | 3-D Reconstruction From Multiple Views | 30 | 35 | 40 | -- | -- | -- |
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| Tutorial No. | Date | Time | Syllabus | Question Paper | Solution |
| 1 | 11/02/2015 | 12:00-13:00 | |||
| 2 | 21/02/2015 | 11:00-12:00 | |||
| 3 | 24/03/2015 | 08:00-09:00 | |||
| 4 | 21/04/2015 | 08:00-09:00 |
Term Project Allotment List
Marks Distribution
Logistic Details
| Important Dates | |
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Finalizing the groups by students |
28/01/2015 |
| Choice of TPA by students |
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TPA Assignment to each group |
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Interim TPA Review(optional) |
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Final TPA Demo |
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| Mid Semester Exam | 11/03/2015 (12:00 - 13:00) |
| End Semester Exam | 01/05/2015 |
Self Study Topics