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| Publications | |
|
2013 | |
|
Recognizing Activities via Bag of Words for Attribute Dynamics | |
|
Anomaly Detection and Localization in Crowded Scenes | |
|
Latent Dirichelet Allocation
Models for Image Classification | |
|
Biologically-inspired Object Tracking Using
Center-surround Mechanisms | |
| Surveillance of Crowded Environments: Modeling the Crowd by
its Global Properties A. Chan and N. Vasconcelos in Modeling, Simulation and Visual Analysis of Crowds to appear. | |
|
| |
| 2012 | |
|
Minimum Probability of Error Image
Retrieval: From Visual Features to Image
Semantics | |
|
Endoscopic image analysis in semantic
space | |
| Learning
Optimal Embedded Cascades Mohammad J. Saberian and Nuno Vasconcelos IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 34(10), 2005-2018, October 2012 [ps] [pdf] | |
| Holistic Context Models for Visual
Recognition N. Rasiwasia and N. Vasconcelos IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 34 (5), 902-917, May 2012 © IEEE [ps] [pdf] [supplement/ps] [supplement/pdf] | |
|
Counting People with Low-level
Features and Bayesian Regression | |
|
On the connections between
saliency and tracking | |
|
Recognizing
Activities by Attribute Dynamics W. Li and N. Vasconcelos to appear in Proceedings of Advances in Neural Information Processing Systems (NIPS) Lake Tahoe, Nevada, United States, 2012 | |
|
Scene Recognition on the Semantic
Manifold | |
| Recognition in Ultrasound Videos: Where am
I? R. Kwitt, N. Vasconcelos, S. Razzaque and S. Aylward Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'12), (Young Scientist award) Nice, 2012. [ps] [pdf] | |
| On
the Regularization of Image Semantics by Modal Expansion J. Costa Pereira, and Nuno Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, 2012. © IEEE [ps] [pdf] [demo] | |
| Boosting Algorithms
for Simultaneous Feature Extraction and Selection Mohammad J. Saberian and Nuno Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Providence, RI, 2012. © IEEE [ps] [pdf][Code] | |
| 2011 | |
| Generalized
Stauffer-Grimson Background Subtraction for Dynamic Scenes A. B. Chan, V. Mahadevan and N. Vasconcelos Machine Vision and Applications, vol. 22(5), 751-766, 2011. [ps] [pdf] | |
| Multiclass Boosting: Theory and
Algorithms Mohammad J. Saberian and Nuno Vasconcelos . In Proc. Neural Information Processing Systems (NIPS), Granada, Spain, Dec 2011. [ps] [pdf][code] | |
| Maximum Covariance
Unfolding - Manifold Learning for Bimodal Data V. Mahadevan, C-W. Wong, J Costa-Pereira, T.T. Liu, N. Vasconcelos and L.K. Saul In Proc. Neural Information Processing Systems Dec 2011 [ps] [pdf] | |
| Learning
Pit Pattern Concepts for Gastroenterological Training R. Kwitt, N. Rasiwasia, N. Vasconcelos, A. Uhl, M. Hafner, F. Wr Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'11), Toronto, Sept 2011 [ps] [pdf] | |
| Biologically Plausible Detection of
Amorphous Objects in the Wild Sunhyoung Han and Nuno Vasconcelos, IEEE CVPR Workshop on Biologically-Consistent Vision, pp. 17-24, June 2011.© IEEE [ps][pdf] | |
| Automatic Initialization and Tracking
Using Attentional Mechanisms V. Mahadevan and N. Vasconcelos, IEEE CVPR Workshop on Biologically-Consistent Vision, June 2011.© IEEE [ps][pdf] | |
| Adapted Gaussian
Models for Image Classification M. Dixit, N. Rasiwasia and N. Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, 2011. © IEEE [ps] [pdf] | |
| TaylorBoost: First
and Second Order Boosting Algorithms with Explicit Margin
Control Mohammad J. Saberian, Hamed Masnadi-Shirazi and Nuno Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, 2011. © IEEE [ps] [pdf][code] | |
| 2010 | |
| Cost-Sensitive
Boosting Hamed Masnadi-Shirazi and Nuno Vasconcelos IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 32(2), 294, March 2010 . © IEEE [ps] [pdf] | |
| Biologically
Plausible Saliency Mechanisms Improve Feedforward Object
Recognition Sunhyoung Han and Nuno Vasconcelos Vision Research, vol. 50(22), 2295-2307, October 2010 [pdf] [doi:10.1016/j.visres.2010.05.034] | |
| A Novel Approach to
FRUC using Discriminant Saliency and Frame Segmentation N. Jacobson, Y-L. Lee, V. Mahadevan, N. Vasconcelos and T.Q. Nguyen IEEE Transactions on Image Processing, vol. 19(11) ,2924-2934, Nov. 2010. © IEEE [ps] [pdf] | |
| Spatiotemporal
Saliency in Highly Dynamic Scenes V. Mahadevan and N. Vasconcelos IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 32(1), 171-177, January 2010. © IEEE [ps] [pdf] [dataset] | |
| Variable
margin losses for classifier design. Hamed Masnadi-Shirazi and Nuno Vasconcelos . In Proc. Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec 2010. [ps] [pdf] | |
| A
biologically plausible network for the Computation of Orientation
Dominance Kritika Muralidharan and Nuno Vasconcelos . In Proc. Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec 2010. [ps] [pdf] | |
| Boosting
Classifer Cascades Mohammad J. Saberian and Nuno Vasconcelos . In Proc. Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec 2010. [ps] [pdf] | |
|
| |
| A New Approach to
Cross-Modal Multimedia Retrieval N. Rasiwasia, J. Costa Pereira, E. Coviello, G. Doyle, G.R.G. Lanckriet, R. Levy, N. Vasconcelos ACM Proceedings of the 15th international conference on Multimedia, (best student paper award) Florence, Italy, Oct 2010. [ps] [pdf] | |
| Motion Vector
Refinement for FRUC Using Saliency and Segmentation N. Jacobson, Y-L. Lee, V. Mahadevan, N. Vasconcelos and T.Q. Nguyen IEEE International Conference on Multimedia & Expo (ICME), Singapore, Jul 2010 © IEEE [ps] [pdf] | |
| Risk minimization,
probability elicitation, and cost-sensitive SVMs Hamed Masnadi-Shirazi and Nuno Vasconcelos Proc. International Conference on Machine Learning (ICML), June 2010. [ps] [pdf] | |
| On the Design of
Robust Classifiers for Computer Vision Hamed Masnadi-Shirazi, Vijay Mahadevan and Nuno Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, 2010. © IEEE [ps] [pdf] | |
| Anomaly Detection
in Crowded Scenes V. Mahadevan, W. Li, V. Bhalodia and N. Vasconcelos Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, 2010. © IEEE [ps] [pdf] [dataset] | |
| 2009 | |
| Layered Dynamic
Textures Antoni B. Chan and Nuno Vasconcelos IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 31(10),1862-1879, October 2009. © IEEE [ps] [pdf] | |
| Bayesian Poisson
Regression for Crowd Counting Antoni B. Chan and Nuno Vasconcelos IEEE International Conference on Computer Vision, Kyoto, September 2009. © IEEE [ps] [pdf] | |
| Discriminant
saliency, the detection of suspicious coincidences, and applications to
visual recognition D. Gao, S. Han, N. Vasconcelos, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31(6), pp. 989-1005, June 2009. © IEEE [ps][pdf] [doi:10.1109/TPAMI.2009.27] | |
| Fluoroscopic tumour
tracking for image-guided lung cancer radiotherapy T. Lin, L. Cervino, X. Tang, N. Vasconcelos, and S. Jiang. Physics in Medicine and Biology, Vol 54(4), 981-992, February 2009. [ps][pdf] [doi:10.1088/0031-9155/54/4/011] | |
| Minimum Bayes error
features for visual recognition G. Carneiro and N. Vasconcelos Image and Vision Computing, Vol 27(1), 131-140, January 2009. [ps][pdf] | |
| Decision-theoretic
saliency: computational principles, biological plausibility, and
implications for neurophysiology and psychophysics D. Gao and N. Vasconcelos. Neural Computation, 21, 239-271, January 2009. [ps][pdf] | |
| Natural Image
Statistics and Low-complexity Feature Selection M. Vasconcelos and N. Vasconcelos IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 31(2), pp. 228-244, February 2009. © IEEE [ps][pdf] | |
| Holistic Context
Modeling using Semantic Co-occurrences N. Rasiwasia and N. Vasconcelos In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, June 2009. © IEEE [pdf] | |
| Variational Layered
Dynamic Textures A. B. Chan and N. Vasconcelos In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, June 2009. © IEEE [pdf] | |
| Saliency Based
Discriminant Tracking V. Mahadevan and N. Vasconcelos In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, June 2009. © IEEE [pdf] | |
| Analysis of Crowded
Scenes using Holistic Properties A. B. Chan, M. Morrow, and N. Vasconcelos In 11th IEEE Intl. Workshop on Performance Evaluation of Tracking and Surveillance (PETS 2009), Miami, June 2009. © IEEE [pdf] | |
| Derivations for the
Layered Dynamic Texture and Temporally-Switching Layered Dynamic
Texture A. B. Chan and N. Vasconcelos Technical Report SVCL-TR-2009-01, June 2009. [pdf] | |
| 2008 | |
| On the plausibility
of the discriminant center-surround hypothesis for visual
saliency D. Gao, V. Mahadevan, and N. Vasconcelos. Journal of Vision, 8(7):13, 1-18, June 2008. [doi:10.1167/8.7.13.] [ps][pdf] | |
| 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] | |
| On the Design of
Loss Functions for Classification: theory, robustness to outliers, and
SavageBoost. Hamed Masnadi-Shirazi and Nuno Vasconcelos . In Proc. Neural Information Processing Systems (NIPS), Vancouver, Canada, Dec 2008. [ps] [pdf] | |
| Unsupervised Moving
Target Detection in Dynamic Scenes V. Mahadevan and N. Vasconcelos. Army Science Conference, Orlando, FL, Dec 2008. [ps][pdf] | |
| Image Retrieval
using Query by Contextual Example N. Rasiwasia and N. Vasconcelos. ACM International Conference on Multimedia Information Retrieval (ACM-MIR), Vancouver, Canada, Oct 2008. [ps][pdf] | |
| Complex
discriminant features for object classification S. Han and N. Vasconcelos. International Conference on Image Processing (ICIP), (best student paper award) San Diego, California, Oct. 2008. © IEEE [ps][pdf] | |
| A Systematic Study
of the role of Context on Image Classification N. Rasiwasia and N. Vasconcelos. International Conference on Image Processing (ICIP), San Diego, California, Oct. 2008. © IEEE [ps][pdf] | |
| 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] | |
| Scene
Classification with Low-dimensional Semantic Spaces and Weak
Supervision N. Rasiwasia and N. Vasconcelos. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, June 2008. © IEEE, [ps][pdf] | |
| Background
Subtraction in Highly Dynamic Scenes V. Mahadevan and N. Vasconcelos. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, June 2008. © IEEE, [ps][pdf] | |
| A Study of Query by
Semantic Example N. Rasiwasia and N. Vasconcelos. 3rd International Workshop on Semantic Learning and Applications in Multimedia, Anchorage, June 2008. © IEEE, [ps][pdf] | |
| Object-based
regions of interest for image compression S. Han and N. Vasconcelos, Data Compression Conference (DCC), pp 132-141 Snowbird, Utah, Mar. 2008. [ps] [pdf] | |
| 2007 | |
| 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] | |
| From Pixels to
Semantic Spaces: Advances in Content-Based Image Retrieval N. Vasconcelos IEEE Computer, Vol. 40(7), pp. 20-26, July 2007.© IEEE,[ps][pdf] | |
| 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,[ps][pdf] | |
| 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, December 2007. [ps] [pdf] | |
| 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, October 2007. © IEEE, [ps] [pdf] | |
| 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, October 2007. © IEEE, [ps] [pdf] | |
| Discriminant
Interest Points are Stable D. Gao and N. Vasconcelos. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, MN, June 2007. © IEEE, [ps][pdf] | |
| 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, June 2007. © IEEE, [ps][pdf] | |
| Asymmetric
Boosting Hamed Masnadi-Shirazi and Nuno Vasconcelos. Proceedings of International Conference on Machine Learning, Corvallis, OR, June 2007. [ps][pdf] | |
| 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, June 2007. [ps][pdf] (updated version) (this old version accidently truncated the last dimension of the "wine" dataset [ps][pdf]) | |
| 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] | |
| 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] | |
| 2006 | |
| Image Compression
using Object-based Regions of Interest S. Han, N. Vasconcelos Proceedings of the International Conference on Image Processing pp. 3097-3100 Atlanta, Georgia, October 2006. © IEEE [ps][pdf] | |
| 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, August 2006. [ps][pdf] | |
| 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, July 2006. [ps][pdf] | |
| 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, June 2006.© IEEE,[ps][pdf] | |
|
Single Image Superresolution Based on Support Vector Regression | |
| 2005 | |
|
A Multiresolution Manifold Distance for
Invariant Image Similarity | |
| Layered Dynamic
Textures A. B. Chan and N. Vasconcelos, Proceedings of Neural Information Processing Systems 19, Vancouver, December 2005. [ps][pdf] | |
|
Mixtures of Dynamic
Textures | |
| 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, August 2005. [ps][pdf] | |
|
Probabilistic Kernels for the
Classification of Auto-Regressive Visual Processes | |
|
Integrated learning of saliency, complex
features, and object detectors from cluttered scenes | |
| 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, June 2005.© IEEE ,[ps][pdf] | |
|
Classification and Retrieval of Traffic
Video using Auto-Regressive Stochastic Processes | |
|
Minimum Bayes Error Features for Visual
Recognition by Sequential Feature Selection and Extraction | |
|
The EM Algorithm for Layered Dynamic
Textures | |
|
A Bayesian Architecture for Combining
Saliency Detectors | |
| 2004 | |
|
Minimum Probability of Error Image
Retrieval | |
| 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] | |
|
Discriminant Saliency for Visual
Recognition from Cluttered Scenes | |
| Scalable Discriminant Feature Selection for Image Retrieval and
Recognition N. Vasconcelos and M. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, June 2004. © IEEE, [ps][pdf][slides] | |
| 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, May 2004.[ps][pdf][slides] | |
|
Formulating Semantic Image Annotation as a
Supervised Learning Problem | |
|
Efficient Computation of the KL Divergence
between Dynamic Textures | |
|
A Family of Probabilistic Kernels Based on
Information Divergence | |
| 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, December 2003. [ps][pdf]. | |
| 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, June 2003, © IEEE, [ps][pdf] | |
| The design of
end-to-end optimal image retrieval systems N. Vasconcelos Proceedings of International Conference on Artificial Neural Networks, Istanbul, Turkey, June 2003. [ps][pdf] | |
| 2002 | |
| Feature Selection
by Maximum Marginal Diversity N. Vasconcelos Proceedings of Neural Information Processing Systems, Vancouver, Canada, December 2002. [ps][pdf]. | |
| Exploiting Group
Structure To Improve Retrieval Accuracy and Speed in Image
Databases N. Vasconcelos, Proceedings of International Conference on Image Processing, Rochester, New York, September 2002, © IEEE, [ps][pdf]. | |
| What is the Role of Independence for Visual
Recognition? N. Vasconcelos and G. Carneiro, Proceedings of the European Conference on Computer Vision, Copenhagen, Denmark, May 2002.[ps][pdf] | |
| 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]. | |
| 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, October 2001, © IEEE, [ps][pdf]. | |
| On the Complexity
of Probabilistic Image Retrieval N. Vasconcelos, Proceedings of the International Conference on Computer Vision, Vancouver, Canada, July 2001, © IEEE, [ps][pdf] | |
| Image Indexing with
Mixture Hierarchies N. Vasconcelos Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawai, June 2001, © IEEE, [ps][pdf] | |
| 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]. | |
| Bayesian Video Shot
Segmentation N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 13, Denver, Colorado, December 2000, [ps][pdf]. | |
| A Unifying View of
Image Similarity N. Vasconcelos and A. Lippman, Proceedings of the International Conference on Pattern Recognition, Barcelona, Spain, September 2000, © IEEE, [ps][pdf]. | |
| 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, August 2000, © IEEE, [ps][pdf]. | |
| Learning Over
Multiple Temporal Scales in Image Databases N. Vasconcelos and A. Lippman, Proceedings of the European Conference on Computer Vision, Dublin, Ireland, July 2000, ? Springer, [ps][pdf]. | |
| 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, June 2000, © IEEE, [ps][pdf]. | |
| 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, January 2000. | |
| 1999 | |
| Learning from User
Feedback in Image Retrieval Systems N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 12, Denver, Colorado, December 1999, [ps][pdf]. | |
| 1998 | |
| Learning Mixture
Hierarchies N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 11, Denver, Colorado, December 1998, [ps][pdf]. | |
| Humane Interfaces
to Video A. Lippman, N. Vasconcelos, and G. Iyengar, Proceedings of 32nd Asilomar Conference on Signals, Systems, and Computers, Asilomar, California, November 1998. | |
|
Embedded Mixture Modeling for
Efficient Probabilistic Content-Based Indexing and Retrieval | |
| 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, October 1998, © IEEE, [ps][pdf]. | |
| A Spatiotemporal
Motion Model for Video Summarization N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, June 1998, © IEEE, [ps][pdf] | |
| A Bayesian
Framework for Semantic Content Characterization N. Vasconcelos and A. Lippman, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Santa Barbara, June 1998, © IEEE, [ps][pdf] | |
| A Bayesian
Framework for Content-based Indexing and Retrieval N. Vasconcelos and A. Lippman, Proceedings of IEEE Data Compression Conference Snowbird, Utah, March 1998, © IEEE, [ps][pdf] | |
| 1997 | |
| Multiresolution
Tangent Distance for Affine Invariant Classification N. Vasconcelos and A. Lippman, Proceedings of Neural Information Processing Systems 10, Denver, Colorado, December 1997, [ps][pdf]. | |
| Content-based
Pre-indexed Video N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Santa Barbara, California, October 1997, © IEEE, [ps][pdf]. | |
| 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, October 1997. | |
| 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, October 1997, © IEEE, [ps][pdf]. | |
| 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, June 1997, © IEEE, [ps][pdf]. | |
| Library-based
Coding: a Representation for Efficient Video Compression and
Retrieval N. Vasconcelos and A. Lippman, Proceedings of IEEE Data Compression Conference, Snowbird, Utah, March 1997, © IEEE, [ps][pdf]. | |
| 1996 | |
| Frame-free
Video N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Lausanne, Switzerland, September 1996, © IEEE, [ps][pdf]. | |
| 1995 | |
| Spatiotemporal
Model-Based Optic Flow Estimation N. Vasconcelos and A. Lippman, Proceedings of International Conference on Image Processing, Washington DC, October 1995, © IEEE, [ps][pdf]. |
Copyright @ 2007 www.svcl.ucsd.edu