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Advances in Image Retrieval and Motion Tracking for Robotics Applications

Dive into the world of computer vision research focusing on image retrieval techniques like Content Based Image Retrieval using methods such as Fuzzy C-Mean clustering and Earth Mover's Distance. Explore the realm of motion tracking with optical flow technologies and innovative applications in robotics. Discover key papers in the field and potential topics for further exploration.

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Advances in Image Retrieval and Motion Tracking for Robotics Applications

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  1. Computer Vision REUWeek 6 Adam Kavanaugh

  2. This week in review • Worked toward narrowing down a research topic • Read many papers in both 2004 and 2005 IEEE CVPR conference proceedings as well as others. • Mostly stuck with papers in the areas of: • Image retrieval (general and medical) • Motion • Tracking

  3. Content Based Image Retrieval • Basics of Image Retrieval • Extract features or distinctive information from a database and a query • Use a type of distance function to find the most similar matches • Improve query results by getting user feedback, or use a learning approach to limit user involvement

  4. Image Retrieval Papers • Recurring Methods used: • Fuzzy C-Mean clustering • Earth Mover’s Distance • Support Vector Machines • Some Papers: • Hoi, S.C.H.; Lyu, M.R., "A semi-supervised active learning framework for image retrieval" • Grauman, K.; Darrell, T., "Efficient image matching with distributions of local invariant features" • Hertz, T.; Bar-Hillel, A.; Weinshall, D., "Learning distance functions for image retrieval"

  5. Image Retrieval as a Topic • Working with Dr. Sugaya to perform retrieval of gene mapping MRI’s • Gene mapping in this context is disease association

  6. Motion and Tracking • Primary interest in motion and tracking falls into the category of Robotics Applications and/or previous work with optical flow. • Would like to see some kind of relevant application come out of the work on optical flow.

  7. Some Topic Ideas in Motion • The presentations of the COCOA system and similar Aerial tracking applications are of interest. • Applying SIFT descriptors to give more accurate motion fields in Optical Flow. • Navigation and obstacle detection in motion

  8. Some More Papers • Optical Flow • Lei Yuan; Jinzong Li; Bing Zhu; Yulong Qiao, "A Discontinuity-preserving Optical Flow Algorithm" • Zhimin Fan; Ying Wu; Ming Yang, "Multiple collaborative kernel tracking" • Tracking • Greenspan, M.; Limin Shang; Jasiobedzki, P., "Efficient tracking with the Bounded Hough Transform" • Freedman, D.; Turek, M.W., "Illumination-invariant tracking via graph cuts"

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