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» Learning Visual Attributes
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TCSV
2008
297views more  TCSV 2008»
15 years 2 months ago
Activity Analysis, Summarization, and Visualization for Indoor Human Activity Monitoring
Abstract--In this work, we study how continuous video monitoring and intelligent video processing can be used in eldercare to assist the independent living of elders and to improve...
Zhongna Zhou, Xi Chen, Yu-Chia Chung, Zhihai He, T...
CVIU
2004
152views more  CVIU 2004»
15 years 2 months ago
Detecting image orientation based on low-level visual content
Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection al...
Yongmei Michelle Wang, HongJiang Zhang
127
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PUC
2007
84views more  PUC 2007»
15 years 2 months ago
Interacting with mobile services: an evaluation of camera-phones and visual tags
We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a userexperience study is described in which participants were both observed learning ...
Eleanor F. Toye, Richard Sharp, Anil Madhavapeddy,...
ICRA
2010
IEEE
111views Robotics» more  ICRA 2010»
15 years 1 months ago
Visual path following on a manifold in unstructured three-dimensional terrain
— This paper describes the design and testing of a technique to enable long-range autonomous navigation using a stereo camera as the only sensor. During a learning phase, the rov...
Paul Timothy Furgale, Timothy D. Barfoot
ICML
1999
IEEE
16 years 3 months ago
Lazy Bayesian Rules: A Lazy Semi-Naive Bayesian Learning Technique Competitive to Boosting Decision Trees
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
Zijian Zheng, Geoffrey I. Webb, Kai Ming Ting