BMVC 2002 - PDF Preprint Papers

BMVC 2002

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BMVC
2002

241views Computer Vision» more BMVC 2002»

Adaptive Learning of Statistical Appearance Models for 3D Human Tracking

13 years 7 months ago

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A likelihood formulation for human tracking is presented based upon matching feature statistics on the surface of an articulated 3D body model. A benefit of such a formulation ove...

Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...

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Id	Views	Title	Status

1	241	Adaptive Learning of Statistical Appearance Models for 3D Human Tracking	claim
2	236	A Comparison of Face Verification Algorithms using Appearance Models	claim
3	233	Spatial and Probabilistic Modelling of Pedestrian Behaviour	claim
4	223	Blending Images for Texturing 3D Models	claim
5	220	Invariant Features from Interest Point Groups	claim
6	219	Real Time Robust Template Matching	claim
7	219	Detecting Planes In An Uncalibrated Image Pair	claim
8	216	The Geometry of Dynamic Scenes - On Coplanar and Convergent Linear Motions Embedded in 3D Static Scenes	claim
9	214	Image Fusion Using Complex Wavelets	claim
10	197	Comparing Variations on the Active Appearance Model Algorithm	claim
11	186	Robust Wide Baseline Stereo from Maximally Stable Extremal Regions	claim
12	172	Bundle adjustment: a fast method with weak initialisation	claim
13	156	Tightly Integrated Sensor Fusion for Robust Visual Tracking	claim
14	155	Component-based LDA Face Descriptor for Image Retrieval	claim
15	154	Improving architectural 3D reconstruction by plane and edge constraining	claim
16	152	Randomized RANSAC with T(d, d) test	claim
17	150	Low Density Feature Point Matching for Articulated Pose Identification	claim
18	142	Saliency of Interest Points under Scale Changes	claim
19	135	Teleoperating ROBONAUT: A case study	claim
20	130	Maximum Likelihood 3D Reconstruction from One or More Images under Geometric Constraints	claim
21	129	Orientation Correlation	claim
22	123	Real-time gesture recognition using deterministic boosting	claim
23	116	g-HDAF Multiresolution Deformable Models for Shape Modeling and Reconstruction	claim
24	115	A New Constrained Parameter Estimator: Experiments in Fundamental Matrix Computation	claim
25	113	Novel View Specification and Synthesis	claim
26	111	Object Recognition by a Cascade of Edge Probes	claim
27	110	Alignment using Spectral Clusters	claim
28	110	Estimating Lighting Direction and Classifying Textures	claim
29	108	Practical Generation of Video Textures using the Auto-Regressive Process	claim
30	104	A comparative study of two object recognition methods	claim
31	104	Modelling Facial Behaviours	claim
32	102	A Qualitative, Multi-scale Grammar For Image Description and Analysis	claim
33	100	Speed v. Accuracy for High Resolution Colour Texture Classification	claim
34	99	Modelling life cycle related and individual shape variation in biological specimens	claim
35	96	3D reconstruction, omnidirectional vision and understanding of scenes	claim
36	95	Integrated Shape and Pose Modelling	claim
37	88	Using Points at Infinity for Parameter Decoupling in Camera Calibration	claim
38	81	Texture classification with thousands of features	claim

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