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» Learning a Classification Model for Segmentation
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PERCOM
2007
ACM
16 years 4 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
ICMCS
2006
IEEE
131views Multimedia» more  ICMCS 2006»
15 years 11 months ago
Self-Supervised Learning for Robust Video Indexing
The performance of video analysis and indexing algorithms strongly depends on the type, content and recording characteristics of the analyzed video. Current video indexing approac...
Ralph Ewerth, Bernd Freisleben
MM
2006
ACM
103views Multimedia» more  MM 2006»
15 years 10 months ago
Progressive cut
Recently, interactive image cutout technique becomes prevalent for image segmentation problem due to its easy-to-use nature. However, most existing stroke-based interactive object...
Chao Wang, Qiong Yang, Mo Chen, Xiaoou Tang, Zhong...
CVPR
2006
IEEE
16 years 6 months ago
Correlated Label Propagation with Application to Multi-label Learning
Many computer vision applications, such as scene analysis and medical image interpretation, are ill-suited for traditional classification where each image can only be associated w...
Feng Kang, Rong Jin, Rahul Sukthankar
ICIP
2005
IEEE
16 years 6 months ago
Learning hidden semantic cues using support vector clustering
This paper presents a method to infer hidden semantic cues by accumulating the knowledge learned from relevance feedback sessions. We propose to explicitly represent a semantic sp...
Jia-Wen Tung, Chiou-Ting Hsu