Semantic Video Indexing (Application of novel probabilistic graphical architectures for video indexing)

  1. " Probabilistic Multimedia Objects Multijects: A novel Approach to Indexing and Retrieval in Multimedia Systems ", Proc. I.E.E.E. International Conference on Image Processing, Volume 3, pages 536-540, Oct 1998, Chicago, IL
  2. “A Factor Graph Framework for Semantic Indexing and Retrieval in Video”, Content-Based Access of Image and Video Library 2000 June 12, 2000 held in conjunction with the IEEE Computer Vision and Pattern Recognition 2000.
  3.  “Semantic Video Indexing using a probabilistic framework”, IAPR International Conference on Pattern Recognition, Barcelona, Spain, 3-8 September 2000
  4. “A Probabilistic Framework for Semantic Indexing and Retrieval in Video”, IEEE International Conference on Multimedia and Expo, New York, 31 July-2 August 2000
  5. “Inferring Semantic Concepts for Video Indexing and Retrieval”, IEEE Intl. Conference on Image Processing, Vancouver, Canada, September 2000
  6.  “Probabilistic Semantic Video Indexing”, to be presented at NIPS 2000, Denver, Colorado
  7. “Semantic Filtering of Video Content”, to be presented at SPIE, Storage and Retrieval for Media Databases, Jan 2001, San Jose
  8. “A Probabilistic Framework for Recognizing Audio-visual Semantics”, presented at the ARL Workshop FEDLAB 2001.
  9. “Detecting semantic concepts using context and audio-visual features”, presented at the workshop on Event Detection held in conjunction with ICCV 2001.
  10. “Classifying Motion Picture Soundtrack for Video Indexing”, presented at the second International Conference on Multimedia in Japan, 2001.
  11. “Duration-dependent input-output Markov models for audio-visual event detection”, presented at the second International Conference on Multimedia in Japan, 2001.
  12. “Recognizing High-level Concepts for Video Indexing”, to be presented at the CBMI 2001
  13. “Recognizing High-level Audio-visual Concepts using Context”, to be presented at the ICIP 2001

Video Segmentation and Matching

  1. "A High Performance Shot Boundary Detection Algorithm using multiple cues" , Proc. I.E.E.E. International Conference on Image Processing, Volume 2, pages 884-887, Oct 1998, Chicago, IL.
  2. “A Novel Scheme for fast and efficient video sequence matching using compact signatures”, Proc. SPIE, Storage and Retrieval for Media Databases 2000, M. Naphade et al, Volume 3972, pages 564-572, Jan 2000, San Jose, CA
  3. “Stochastic modeling of soundtrack for efficient segmentation and indexing of video”, Proc. SPIE, Storage and Retrieval for Media Databases 2000, M. Naphade et al, Volume 3972, pages 168-176, Jan 2000, San Jose, CA
  4. “Multimodal pattern matching for audio-visual query and retrieval”, Proc. SPIE, Storage and Retrieval for Media databases, M. Naphade et al, Voulme 4315, pages 188-195, Jan 2001, San Jose, CA.
  5. “Supporting Audio-visual Query using dynamic programming”, to be presented at the ACM Multimedia, Oct 2001.

Learning

  1. “Learning Sparse Multiple Cause Models”, IAPR International Conference on Pattern Recognition, Barcelona, Spain, 3-8 September 2000
  2. “Image Classification using labeled and unlabeled images”, to be presented at the SPIE Intl. Symposium on Voice, Video and Data Communications, Program on “Internet Multimedia Management Systems”, Nov 6 2000 Boston

Invited Papers

  1. “Multimedia Understanding: Challenges in the new millennium”, IEEE Intl. Conference on Image Processing, Vancouver, Canada, September 2000
  2. “MARS (Multimedia Analysis and Retrieval System):  A test-bed for video indexing, browsing, searching, filtering and summarization”, T. S. Huang and Milind Naphade, International Workshop on Multimedia Data Storage, Retrieval, Integration and Applications, Hong Kong Polytechnic University EIE Dept., 13-15 January, 2000, (Keynote Speech given by Prof. Thomas Huang)

Papers after joining IBM Research

  1. M. Naphade, C. Lin, J. Smith, B. Tseng and S. Basu, "Learning to Annotate Video Databases", SPIE Storage and Retrieval for Media Databases, Jan 2002, San Jose, CA
  2. J. Smith, S. Srinivasan, A. Amir, S. Basu, G. Iyengar, C. Lin, Milind Naphade, D. Ponceleon, and B Tseng, "Integrating Features, Models, and Semantics for TREC Video Retrieval," NIST TREC-10 Text Retrieval Conference, Gaithersburg, Maryland, November 2001.
  3. M. Naphade and S. Basu, "Special Session on Statistical Learning in Multimedia Processing", IEEE International Conference on Acoustics, Speech and Signal Processing, May 2002, Orlando, FL
  4. S. Basu, M. Naphade and J. Smith, "A Statistical Modeling Approach to Content-based Video Retrieval", IAPR International Conference on Pattern Recognition, Aug 2002, Quebec City, Canada
  5. M. Naphade,  "Statistical Media Analysis in Video Indexing", SPIE ITCOM, Internet Multimedia Management Systems III, Aug 2002, Boston, MA
  6. M. Naphade, C. Lin and J. Smith, "Learning Semantic Multimedia Representations from a Small Set of Examples ", IEEE International Conference on Multimedia and Expo, Aug 2002, Lusanne, Switzerland.
  7. M. Naphade, S. Basu, J. Smith, C. Lin and B. Tseng, "Modeling Semantic Concepts to Support Query by Keywords in Video", IEEE International Conference on Image Processing, Sep 2002, Rochester, NY.
  8. M. Naphade, "Statistical Techniques in Video Data Management", to be published in IEEE Multimedia Signal Processing Workshop, Dec 2002, US Virgin Islands
  9. M. Naphade and J. Smith, "The Role of Classifiers in Video Indexing", to be published in Proceedings, SPIE Storage and Retrieval for Media Databases, Jan 2003, San Jose, CA