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MONET
2007
106views more  MONET 2007»
13 years 7 months ago
Shakra: Tracking and Sharing Daily Activity Levels with Unaugmented Mobile Phones
This paper explores the potential for use of an unaugmented commodity technology—the mobile phone— as a health promotion tool. We describe a prototype application that tracks t...
Ian Anderson, Julie Maitland, Scott Sherwood, Loui...
CVPR
2011
IEEE
13 years 3 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman
ICMCS
2009
IEEE
168views Multimedia» more  ICMCS 2009»
13 years 5 months ago
Human activity recognition based on the blob features
In this paper, we present a novel approach for human activities recognition in the video. We analyze human activities in the sequential frames because human activities can be cons...
Jie Yang, Jian Cheng, Hanqing Lu
AVSS
2006
IEEE
14 years 1 months ago
A Smith-Waterman Local Alignment Approach for Spatial Activity Recognition
In this paper we address the spatial activity recognition problem with an algorithm based on Smith-Waterman (SW) local alignment. The proposed SW approach utilises dynamic program...
Daniel E. Riedel, Svetha Venkatesh, Wanquan Liu
AI
2004
Springer
13 years 7 months ago
A selective sampling approach to active feature selection
Feature selection, as a preprocessing step to machine learning, has been very effective in reducing dimensionality, removing irrelevant data, increasing learning accuracy, and imp...
Huan Liu, Hiroshi Motoda, Lei Yu