Shape-and-Behavior Encoded Tracking of Bee Dances
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Rama Chellappa | Ashok Veeraraghavan | Mandyam V. Srinivasan | R. Chellappa | M. Srinivasan | A. Veeraraghavan
[1] Hsi-Jian Lee,et al. Determination of 3D human body postures from a single view , 1985, Comput. Vis. Graph. Image Process..
[2] L. R. Rabiner,et al. A probabilistic distance measure for hidden Markov models , 1985, AT&T Technical Journal.
[3] R. Chellappa,et al. Recursive 3-D motion estimation from a monocular image sequence , 1990 .
[4] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[5] R. Morse. The Dance Language and Orientation of Bees , 1994 .
[6] Fabrizio Mura,et al. Visual control of altitude and speed in a flying agent , 1994 .
[7] Zhang,et al. Honeybee navigation en route to the goal: visual flight control and odometry , 1996, The Journal of experimental biology.
[8] Michael Isard,et al. Contour Tracking by Stochastic Propagation of Conditional Density , 1996, ECCV.
[9] Christoph Bregler,et al. Learning and recognizing human dynamics in video sequences , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[10] Jun S. Liu,et al. Sequential Monte Carlo methods for dynamic systems , 1997 .
[11] Michael J. Black,et al. A probabilistic frameworkfor matching temporal trajectories , 1998, ICCV 1998.
[12] H. Damasio,et al. IEEE Transactions on Pattern Analysis and Machine Intelligence: Special Issue on Perceptual Organization in Computer Vision , 1998 .
[13] Michael Isard,et al. Learning Multi-Class Dynamics , 1998, NIPS.
[14] Michael Isard,et al. A mixed-state condensation tracker with automatic model-switching , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).
[15] Gregory D. Hager,et al. Efficient Region Tracking With Parametric Models of Geometry and Illumination , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[16] Vladimir Pavlovic,et al. A dynamic Bayesian network approach to figure tracking using learned dynamic models , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[17] José M. F. Moura,et al. Capture and Representation of Human Walking in Live Video Sequences , 1999, IEEE Trans. Multim..
[18] Dorin Comaniciu,et al. Real-time tracking of non-rigid objects using mean shift , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[19] Michael Isard,et al. Learning and Classification of Complex Dynamics , 2000, IEEE Trans. Pattern Anal. Mach. Intell..
[20] Cristian Sminchisescu,et al. Covariance scaled sampling for monocular 3D body tracking , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.
[21] Heinrich H. Bülthoff,et al. Insect Inspired Visual Control of Translatory Flight , 2001, ECAL.
[22] Panos J. Antsaklis,et al. Hierarchical Control of Piecewise Linear Hybrid Dynamical Systems Based on Discrete Abstractions , 2001 .
[23] Ramakant Nevatia,et al. 3D tracking of human locomotion: a tracking as recognition approach , 2002, Object recognition supported by user interaction for service robots.
[24] H. Shum,et al. Learning A Highly Structured Motion Model for 3D Human Tracking , 2002 .
[25] Timothy J. Robinson,et al. Sequential Monte Carlo Methods in Practice , 2003 .
[26] F. Dellaert,et al. A Rao-Blackwellized particle filter for EigenTracking , 2004, CVPR 2004.
[27] Rama Chellappa,et al. Visual tracking and recognition using appearance-adaptive models in particle filters , 2004, IEEE Transactions on Image Processing.
[28] N. Vaswani,et al. Change detection in partially observed nonlinear dynamic systems with unknown change parameters , 2004, Proceedings of the 2004 American Control Conference.
[29] T. Seeley. The tremble dance of the honey bee: message and meanings , 1992, Behavioral Ecology and Sociobiology.
[30] Yoram Singer,et al. The Hierarchical Hidden Markov Model: Analysis and Applications , 1998, Machine Learning.
[31] James M. Rehg,et al. Learning and inference in parametric switching linear dynamic systems , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[32] Daniel Freedman,et al. Illumination-invariant tracking via graph cuts , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[33] James M. Rehg,et al. Parameterized Duration Mmodeling for Switching Linear Dynamic Systems , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[34] Namrata Vaswani,et al. Additive Change Detection in Nonlinear Systems With Unknown Change Parameters , 2007, IEEE Transactions on Signal Processing.
[35] James M. Rehg,et al. Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems , 2008, International Journal of Computer Vision.
[36] Amit K. Roy-Chowdhury,et al. Integrating Motion, Illumination, and Structure in Video Sequences with Applications in Illumination-Invariant Tracking , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.