Adaptive background mixture models for real-time tracking
- C. Stauffer, W. Grimson
- Computer ScienceProceedings. IEEE Computer Society Conference on…
- 23 June 1999
This paper discusses modeling each pixel as a mixture of Gaussians and using an on-line approximation to update the model, resulting in a stable, real-time outdoor tracker which reliably deals with lighting changes, repetitive motions from clutter, and long-term scene changes.
Learning Patterns of Activity Using Real-Time Tracking
- C. Stauffer, W. Grimson
- Computer ScienceIEEE Transactions on Pattern Analysis and Machine…
- 1 August 2000
This paper focuses on motion tracking and shows how one can use observed motion to learn patterns of activity in a site and create a hierarchical binary-tree classification of the representations within a sequence.
Unsupervised Activity Perception in Crowded and Complicated Scenes Using Hierarchical Bayesian Models
- Xiaogang Wang, Xiaoxu Ma, W. Grimson
- Computer ScienceIEEE Transactions on Pattern Analysis and Machine…
- 1 April 2008
A novel unsupervised learning framework to model activities and interactions in crowded and complicated scenes with many kinds of activities co-occurring, and three hierarchical Bayesian models are proposed that advance existing language models, such as LDA and HDP.
Gait analysis for recognition and classification
- L. Lee, W. Grimson
- Computer ScienceProceedings of Fifth IEEE International…
- 20 May 2002
This work describes a representation of gait appearance based on simple features such as moments extracted from orthogonal view video silhouettes of human walking motion that contains enough information to perform well on human identification and gender classification tasks.
Object recognition by computer - the role of geometric constraints
- W. Grimson
- Computer Science
- 4 January 1991
This book describes an extended series of experiments into the role of geometry in the critical area of object recognition, providing precise definitions of the recognition and localization problems, the methods used to address them, the solutions to these problems, and the implications of this analysis.
Using adaptive tracking to classify and monitor activities in a site
- W. Grimson, C. Stauffer, R. Romano, L. Lee
- Computer Science, Environmental ScienceProceedings. IEEE Computer Society Conference on…
- 23 June 1998
A vision system that monitors activity in a site over extended periods of time using tracked motion data to calibrate the distributed sensors, to construct rough site models, to classify detected objects, to learn common patterns of activity for different object classes, and to detect unusual activities.
Spatial Latent Dirichlet Allocation
- Xiaogang Wang, W. Grimson
- Computer ScienceNIPS
- 3 December 2007
A topic model Spatial Latent Dirichlet Allocation (SLDA), which better encodes spatial structures among visual words that are essential for solving many vision problems, is proposed and used to discover objects from a collection of images.
Learning Semantic Scene Models by Trajectory Analysis
- Xiaogang Wang, Kinh H. Tieu, W. Grimson
- Computer ScienceEuropean Conference on Computer Vision
- 7 May 2006
An unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from long-term observations of moving objects in the scene is described and novel clustering algorithms which use both similarity and comparison confidence are introduced.
Localizing Overlapping Parts by Searching the Interpretation Tree
- W. Grimson, Tomas Lozano-Perez
- MathematicsIEEE Transactions on Pattern Analysis and Machine…
- 1 April 1987
The approach operates by examining all hypotheses about pairings between sensed data and object surfaces and efficiently discarding inconsistent ones by using local constraints on distances between faces, angles between face normals, and angles of vectors between sensed points.
Trajectory Analysis and Semantic Region Modeling Using Nonparametric Hierarchical Bayesian Models
- Xiaogang Wang, K. Ma, G. Ng, W. Grimson
- Computer ScienceInternational Journal of Computer Vision
- 1 December 2011
The Dual Hierarchical Dirichlet Processes model is extended to a Dynamic Dual-HDP model which allows dynamic update of activity models and online detection of normal/abnormal activities.
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