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| Publications | |
| 2008 | |
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A Study of Query by Semantic Example N. Rasiwasia and N. Vasconcelos. To appear, 3rd International Workshop on Semantic Learning and Applications in Multimedia, Anchorage, June 2008. ©IEEE, [ps][pdf] |
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Decision-theoretic saliency: computational principles, biological plausibility,
and implications for neurophysiology and psychophysics D. Gao and N. Vasconcelos. To appear in Neural Computation, 2008. | |
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On the plausibility of the discriminant center-surround hypothesis
for visual saliency D. Gao, V. Mahadevan, and N. Vasconcelos. To appear in Journal of Vision, 2008. | |
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Natural Image Statistics and Low-complexity Feature Selection Vasconcelos M., Vasconcelos, N. To appear in IEEE Trans. on Pattern Analysis and Machine Intelligence, 2008. © IEEE [ps][pdf] | |
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Modeling, clustering, and segmenting video with mixtures of dynamic textures A. B. Chan and N. Vasconcelos. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 30(5), pp. 909-926, May 2008. © IEEE [ps][pdf] | |
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Scene Classification with Low-dimensional Semantic Spacesand Weak Supervision N. Rasiwasia and N. Vasconcelos. To appear, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, June 2008. ©IEEE, [ps][pdf] |
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Privacy Preserving Crowd Monitoring: Counting People without People Models or Tracking A. B. Chan, Z. S. J. Liang, and N. Vasconcelos. In, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, June 2008. ©IEEE, [ps][pdf] |
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| 2007 | |
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Bridging the Gap: Query by Semantic Example Rasiwasia, N., Moreno, P. L., Vasconcelos, N. Multimedia, IEEE Transactions on, Vol. 9(5), pp. 923-938, Aug 2007.© IEEE,[ps][pdf] |
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From Pixels to Semantic Spaces: Advances in Content-Based Image Retrieval N. Vasconcelos IEEE Computer, Vol. 40(7), pp. 20-26, July 2007.© IEEE,[pdf] |
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Supervised Learning of Semantic Classes for Image Annotation and Retrieval G. Carneiro, A. B. Chan, P. J. Moreno, and N. Vasconcelos IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 29(3), pp. 394-410, March 2007.© IEEE,[pdf] |
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The discriminant center-surround hypothesis for bottom-up saliency. D. Gao, V. Mahadevan and N. Vasconcelos. In Proc. Neural Information Processing Systems (NIPS), Vancouver, Canada, 2007. [ps] [pdf] |
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High Detection-rate Cascades for Real-Time Object Detection. Hamed Masnadi-Shirazi and Nuno Vasconcelos. Proceedings of IEEE International Conference on Computer Vision (ICCV) , Rio de Janeiro, Brazil, 2007. © IEEE, [ps] [pdf] |
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Bottom-up saliency is a discriminant process D. Gao and N. Vasconcelos. Proceedings of IEEE International Conference on Computer Vision (ICCV) , Rio de Janeiro, Brazil, 2007. © IEEE, [ps] [pdf] |
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Discriminant Interest Points are Stable D. Gao and N. Vasconcelos. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, MN, 2007. © IEEE, [ps][pdf] |
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Classifying Video with Kernel Dynamic Textures A. B. Chan and N. Vasconcelos. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, MN, 2007. © IEEE, [ps][pdf] |
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Asymmetric Boosting Hamed Masnadi-Shirazi and Nuno Vasconcelos. Proceedings of International Conference on Machine Learning, Corvallis, OR, 2007. [ps][pdf] |
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Direct Convex Relaxations of Sparse SVM A. B. Chan, N. Vasconcelos, and G. R. G. Lanckriet. Proceedings of International Conference on Machine Learning, Corvallis, OR, 2007. [ps][pdf] (updated version) (this old version accidently truncated the last dimension of the "wine" dataset [ps][pdf]) |
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Supplemental for "Classifying Video with Kernel Dynamic Textures" A. B. Chan and N. Vasconcelos. Technical Report SVCL-TR-2007-03, April, 2007. [ps][pdf][zip w/ video] |
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Duals of the QCQP and SDP Sparse SVM A. B. Chan, N. Vasconcelos, and G. R. G. Lanckriet. Technical Report SVCL-TR-2007-02, April 2007. [ps][pdf] |
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| 2006 | |
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Using Statistics to Search and Annotate Pictures: an Evaluation of Semantic Image Annotation and Retrieval on Large Databases A. B. Chan, P. J. Moreno, and N. Vasconcelos Proceedings of Joint Statistical Meetings (JSM), Seattle, 2006.[ps][pdf] |
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Weakly Supervised Top-Down Image Segmentation M. Vasconcelos, G. Carneiro, and N. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, New York, 2006.© IEEE,[ps][pdf] |
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| Query By Semantic Example Nikhil Rasiwasia, Nuno Vasconcelos, Pedro J Moreno Proceedings of the International Conference on Image and Video Retrieval LNCS 4071, pp. 51-60 Phoenix, Arizona, 2006. [ps][pdf] |
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| Single Image
Superresolution Based on Support Vector Regression K. Ni, S. Kumar, N. Vasconcelos, and T.Q. Nguyen, Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, Vol. 2, pp. 601-604 Toulouse, France, 2006. © IEEE,[ps][pdf] |
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| Image Compression using Object-based
Regions of Interest Sunhyoung Han, Nuno Vasconcelos Proceedings of the International Conference on Image Processing pp. 3097-3100 Atlanta, Georgia, 2006. [ps][pdf] |
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| 2005 | |
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A Multiresolution Manifold Distance for Invariant Image Similarity
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| Layered Dynamic Textures A. B. Chan and N. Vasconcelos, Proceedings of Neural Information Processing Systems 19, Vancouver, 2005. [ps][pdf] |
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Mixtures of Dynamic Textures |
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| A Database
Centric View of Semantic Image Annotation and Retrieval G. Carneiro and N. Vasconcelos, Proceedings of ACM Conference on Research and Development in Information Retrieval (ACM SIGIR) Salvador, Brazil. 2005. [ps][pdf] |
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Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes |
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Integrated learning of saliency, complex features, and object detectors from cluttered scenes |
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Formulating Semantic Image Annotation as a Supervised Learning Problem G. Carneiro and N. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Diego, 2005.© IEEE,[ps][pdf] |
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Minimum Bayes Error Features for Visual
Recognition by Sequential Feature Selection and Extraction |
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Classification and Retrieval of Traffic Video using Auto-Regressive Stochastic Processes |
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The EM Algorithm for Layered Dynamic Textures |
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The EM Algorithm for Mixtures of Dynamic Textures |
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A Bayesian Architecture for Combining Saliency Detectors |
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| 2004 | |
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Minimum Probability of Error Image
Retrieval |
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On the
Efficient Evaluation of Probabilistic Similarity Functions for Image
Retrieval N. Vasconcelos, IEEE Transactions on Information Theory vol. 50, No.7, pp1482-1496, July 2004.© IEEE,[ps][pdf] |
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Discriminant Saliency for Visual Recognition from Cluttered Scenes |
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Scalable Discriminant Feature Selection for Image
Retrieval and Recognition N. Vasconcelos and M. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2004.© IEEE,[ps][pdf][slides] |
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The
Kullback-Leibler Kernel as a Framework for Discriminant and Localized
Representations for Visual Recognition N. Vasconcelos, P. Ho, and P. Moreno, Proceedings of the European Conference on Computer Vision, Prague, Czech, 2004.[ps][pdf][slides] |
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Formulating Semantic Image Annotation as a Supervised Learning Problem |
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Efficient Computation of the KL Divergence between Dynamic Textures |
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A Family of Probabilistic Kernels Based on Information Divergence |
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| 2003 | |
| A
Kullback-Leibler Divergence Based Kernel for SVM
Classification in Multimedia Applications P. J. Moreno, P. P. Ho, and N. Vasconcelos Proceedings of Neural Information Processing Systems, Vancouver, Canada, 2003. [ps][pdf]. |
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Feature
Selection by Maximum Marginal Diversity: optimality and implications for
visual recognition N. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Madison, Wisconsin, 2003, © IEEE, [ps][pdf] |
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The
design of end-to-end optimal image retrieval systems N. Vasconcelos Proceedings of International Conference on Artificial Neural Networks, Istanbul, Turkey, 2003. [ps][pdf] |
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| 2002 | |
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Feature
Selection by Maximum Marginal Diversity N. Vasconcelos Proceedings of Neural Information Processing Systems, Vancouver, Canada, 2002. [ps][pdf]. |
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What is the Role of Independence for Visual Recognition? N. Vasconcelos and G. Carneiro, Proceedings of the European Conference on Computer Vision, Copenhagen, Denmark, 2002.[ps][pdf] |
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Exploiting Group Structure To Improve Retrieval Accuracy and Speed in
Image Databases N. Vasconcelos, Proceedings of International Conference on Image Processing, Rochester, New York, 2002, © IEEE, [ps][pdf]. |
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| 2001 | |
| Empirical Bayesian Motion
Segmentation N. Vasconcelos and A. Lippman, IEEE Transactions on Pattern Analysis and Machine Inteligence, vol.23, n.2; February 2001, © IEEE, [ps][pdf]. |
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Image
Indexing with Mixture Hierarchies N. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawai, 2001, © IEEE, [ps][pdf] |
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| On the Complexity of Probabilistic
Image Retrieval N. Vasconcelos, Proceedings of the International Conference on Computer Vision, Vancouver, Canada, 2001, © IEEE, [ps][pdf] |
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| Content-based Retrieval from Image
Databases: Current Solutions and Future Directions N. Vasconcelos and M. Kunt, Proceedings of International Conference on Image Processing, Thessaloniki, Greece, 2001, © IEEE, [ps][pdf]. |
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| 2000 | |
| Statistical Models of Video Structure for Content Analysis and
Characterization N. Vasconcelos and A. Lippman, IEEE Transactions on Image Processing, vol. 9, n. 1; January 2000, © IEEE, [ps][pdf]. |
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| Bayesian Video Shot Segmentation N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 13, Denver, Colorado, 2000, [ps][pdf]. |
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| A Unifying View of Image Similarity N. Vasconcelos and A. Lippman, Proceedings of the International Conference on Pattern Recognition, Barcelona, Spain, 2000, © IEEE, [ps][pdf]. |
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| Feature Representations for Image Retrieval: Beyond the Color
Histogram N. Vasconcelos and A. Lippman, Proceedings of the International Conference on Multimedia and Expo, New York, 2000, © IEEE, [ps][pdf]. |
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Learning Over Multiple Temporal Scales in Image Databases N. Vasconcelos and A. Lippman, Proceedings of the European Conference on Computer Vision, Dublin, Ireland, 2000, © Springer, [ps][pdf]. |
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A Probabilistic Architecture for Content-based Image Retrieval N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, South Carolina, 2000, © IEEE, [ps][pdf]. |
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| Bayesian Representations and Learning Mechanisms for Content Based Image
Retrieval N. Vasconcelos and A. Lippman, Proceedings SPIE Conference on Storage and Retrieval for Media Databases, San Jose, California, 2000. |
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| 1999 | |
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Learning from User Feedback in Image Retrieval Systems N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 12, Denver, Colorado, 1999, [ps][pdf]. |
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| 1998 | |
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Learning Mixture Hierarchies N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 11, Denver, Colorado, 1998, [ps][pdf]. |
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Bayesian Modeling of Video Editing and Structure: Semantic Features for Video Summarization and
Browsing N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Chicago, 1998, © IEEE, [ps][pdf]. |
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A Spatiotemporal Motion Model for Video Summarization N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, 1998, © IEEE, [ps][pdf] |
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A Bayesian Framework for Semantic Content Characterization N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, 1998, © IEEE, [ps][pdf] |
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A Bayesian Framework for Content-based Indexing and Retrieval N. Vasconcelos and A. Lippman, Proceedings of IEEE Data Compression Conference Snowbird, Utah, 1998, © IEEE, [ps][pdf] |
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| Humane Interfaces to Video A. Lippman, N. Vasconcelos, and G. Iyengar, Proceedings of 32nd Asilomar Conference on Signals, Systems, and Computers, Asilomar, California, 1998. |
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Embedded Mixture Modeling for Efficient Probabilistic Content-Based Indexing and
Retrieval |
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| 1997 | |
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Multiresolution Tangent Distance for Affine Invariant
Classification N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 10, Denver, Colorado, 1997, [ps][pdf]. |
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Content-based Pre-indexed Video N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Santa Barbara, California, 1997, © IEEE, [ps][pdf]. |
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Pre and Post-Filtering for Low Bit-rate Video Coding N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Santa Barbara, California, 1997. |
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| Towards Semantically Meaningful Feature Spaces for the Characterization of Video
Content N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Santa Barbara, California, 1997, © IEEE, [ps][pdf]. |
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Empirical Bayesian EM-based Motion Segmentation N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, 1997, © IEEE, [ps][pdf]. |
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Library-based Coding: a Representation for Efficient Video Compression and
Retrieval N. Vasconcelos and A. Lippman, Proceedings of IEEE Data Compression Conference, Snowbird, Utah, 1997, © IEEE, [ps][pdf]. |
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| 1996 | |
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Frame-free Video N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Lausanne, Switzerland, 1996, © IEEE, [ps][pdf]. |
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| 1995 | |
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Spatiotemporal Model-Based Optic Flow Estimation N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Washington DC, 1995, © IEEE, [ps][pdf]. |
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