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RECHNER
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Exploring the Space of a Human Action
TemporalBoost for Event Recognition
A General Framework for Temporal Video Scene Segmentation
Recognizing Human Actions in Videos Acquired by Uncalibrated Moving Cameras
A Supervised Learning Framework for Generic Object Detection in Images
Object Tracking across Multiple Independently Moving Aerial Cameras
A Multiview Approach to Tracking People in Crowded Scenes Using a Planar Homography Constraint
View-invariant Alignment and Matching of Video Sequences
Two-Frame Wide Baseline Matching
Tracking across Multiple Cameras with Disjoint Views
A Non-Iterative Greedy Algorithm for Multi-frame Point Correspondence
Human Tracking in Multiple Cameras
Motion Layer Extraction in the Presence of Occlusion Using Graph Cut
Integrating and Employing Multiple Levels of Zoom for Activity Recognition
A Framework for Segmentation of Talk and Game Shows
Recognizing Human Actions in a Static Room
Using Algebraic Functions of Views for Indexing-Based Object Recognition
Scene Detection in Hollywood Movies and TV Shows
Object Based Segmentation of Video Using Color, Motion and Spatial Information
View-Invariance in Action Recognition