BBN VISER TRECVID 2011 multimedia Event Detection System

2011 TREC Video Retrieval Evaluation Notebook Papers

Volumn , Issue , 2011, Pages

  Natarajan, Pradeep ^a   Natarajan, Prem ^a   Manohar, Vasant ^a   Wu, Shuang ^a   Tsakalidis, Stavros ^a   Vitaladevuni, Shiv N ^a   Zhuang, Xiaodan ^a   Prasad, Rohit ^a   Ye, Guangnan ^b   Liu, Dong ^b   Jhuo, I Hong ^b   Chang, Shih Fu ^b   Izadinia, Hamid ^c   Saleemi, Imran ^c   Shah, Mubarak ^c   White, Brandyn ^d   Yeh, Tom ^d   Davis, Larry ^d  

^a BBN TECHNOLOGIES   (United States)

^b Department of Electrical Engineering Columbia University ^*  (United States)

^c UNIVERSITY OF CENTRAL FLORIDA   (United States)

^d Department of Computer Science University of Maryland ^*  (United States)

Author keywords

Automatic speech recognition; BAYCOM; Early fusion; Feature fusion; Late fusion; Low level visual features; Spatio temporal pooling; Videotext OCR

Indexed keywords

ERRORS; IMAGE RETRIEVAL; SEMANTICS; SPEECH RECOGNITION; STATISTICAL METHODS;

AUTOMATIC SPEECH RECOGNITION; BAYCOM; EARLY FUSION; FEATURE FUSION; LATE FUSION; SPATIO-TEMPORAL; VISUAL FEATURE;

BAYESIAN NETWORKS;

EID: 84905259534     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. [Csurka et al. 2004] G. Csurka, C. Dance, L.X. Fan, J. Willamowski, and C. Bray, "Visual Categorization with Bags of Keypoints," in Proc. of ECCV International Workshop on Statistical Learning in Computer Vision, 2004.
2. [Lazebnik et al. 2006] S. Lazebnik, C. Schmid, and J. Ponce, "Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories," in Proc. CVPR, 2006.
3. [Laptev et al. 2008] I. Laptev, M. Marszalek, C. Schmid, and B. Rozenfeld, "Learning Realistic Human Actions from Movies," in Proc. CVPR, 2008.
4. [Jiang et al. 2010] Y.-G. Jiang, X. Zeng, G. Ye, S. Bhattacharya, D. Ellis, M. Shah, and S.-F. Chang, "Columbia-UCF TRECVID2010 Multimedia Event Detection: Combining Multiple Modalities, Contextual Concepts, and Temporal Matching," in NIST TRECVID Workshop, 2010.
5. [Lowe 2004] D. Lowe. Distinctive image features from scale-invariant keypoints. International Journal on Computer Vision, 60:91-110, 2004.
6. [Mikolajczyk et al. 2004] K. Mikoljczyk and C. Schmid. Scale and affine invariant interest point detectors. International Journal of Computer Vision, 60:63-86, 2004.
7. [Laptev 2005] I. Laptev. On space-time interest points. International Journal of Computer Vision, 64:107-123, 2005.
8. [Liu 2011] Jingen Liu, Mubarak Shah, Benjamin Kuipers, and Silvio Savarese, Cross-View Action Recognition via View Knowledge Transfer, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, 2011
9. [Pan et al. 2010] S. J. Pan, X. Ni, J.-T. Sun, Q. Yang, and Z. Chen. Cross-domain sentiment classification via spectral feature alignment. international conference on World Wide Web, New York, NY, USA, 2010.
10. [Torresani et al. 2010] Lorenzo Torresani, Martin Szummer, Andrew Fitzgibbon. Efficient Object Category Recognition Using Classemes. European Conference on Computer Vision, 2010
11. [van de Sande et al. 2010] K. E. A. van de Sande, T. Gevers and C. G. M. Snoek, Evaluating Color Descriptors for Object and Scene Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 32 (9), pages 1582-1596, 2010.
12. [Boureau et al. 2010] Y. Boureau, F. Bach, Y. Le Cun, and J. Ponce, Learning mid-level features for recognition. In CVPR, pages 2559-2566, 2010.
13. [Bay et al. 2008] H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool. Surf: Speeded up robust features. CVIU, 110(3):346-359, 2008.
14. [Chandrasekhar et al. 2011] V. Chandrasekhar, G. Takacs, D. Chen, S. Tsai, Y. Reznik, R. Grzeszczuk, and B. Girod, Compressed histogram of gradients: a low bitrate descriptor, International Journal on Computer Vision, Vol. 94, No. 5, May 2011.
15. [Felzenszwalb et al. 2010] P. Felzenszwalb, R. Girshick, D. McAllester, D. Ramanan. Object Detection with Discriminatively Trained Part Based Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 32, No. 9, September 2010
16. [Viswanathan et al. 2010] S. V. N. Vishwanathan, Zhaonan Sun, Nawanol, Theera-Ampornpunt, Manik Varma. Multiple Kernel Learning and the SMO Algorithm. In Advances in Neural Information Processing Systems 23, pp. 2361-2369, 2010.
17. [Natarajan et al. 2011] P. Natarajan, S. Tsakalidis, V. Manohar, R. Prasad, and P. Natarajan, Unsupervised Audio Analysis for Categorizing Heterogeneous Consumer Domain Videos, in Interspeech, Florence, Aug. 2011.
18. [Vitaladevuni et al. 2011] S. Vitaladevuni, P. Natarajan, R. Prasad, and P. Natarajan, Efficient Orthogonal Matching Pursuit using sparse random projections for scene and video classification, To appear ICCV, Barcelona, 2011.
19. [Manohar et al. 2011] V. Manohar, S. Tsakalidis, P. Natarajan, R. Prasad, and P. Natarajan, Audio-Visual Fusion Using Bayesian Model Combination for Web Video Retrieval, To appear ACM Multimedia, Scottsdale, AZ, Nov. 2011.