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FGR
2000
IEEE
159views Biometrics» more  FGR 2000»
13 years 11 months ago
Gesture Modeling and Recognition Using Finite State Machines
This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
Pengyu Hong, Thomas S. Huang, Matthew Turk
ICASSP
2010
IEEE
13 years 7 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
CVPR
2011
IEEE
13 years 3 months ago
A Segmentation-aware Object Detection Model with Occlusion Handling
The bounding box representation employed by many popular object detection models [3, 6] implicitly assumes all pixels inside the box belong to the object. This assumption makes th...
Tianshi Gao, Benjamin Packer, Daphne Koller
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 9 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
NIPS
2004
13 years 8 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...