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» Using Maximum Entropy for Automatic Image Annotation
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ICIP
2010
IEEE
13 years 5 months ago
Ball event recognition using hmm for automatic tennis annotation
A key element for video indexing and summarisation is the description of isolated events and actions. In the context of many sports the motion of the ball plays an essential role ...
Ibrahim Almajai, Josef Kittler, Teofilo de Campos,...
CVPR
2010
IEEE
14 years 1 months ago
Semantic Context Modeling with Maximal Margin Conditional Random Fields for Automatic Image Annotation
Context modeling for Vision Recognition and Automatic Image Annotation (AIA) has attracted increasing attentions in recent years. For various contextual information and resources,...
Yu Xiang, Xiangdong Zhou, Zuotao Liu, Tat-seng chu...
VLSISP
1998
111views more  VLSISP 1998»
13 years 7 months ago
Quantitative Analysis of MR Brain Image Sequences by Adaptive Self-Organizing Finite Mixtures
This paper presents an adaptive structure self-organizing finite mixture network for quantification of magnetic resonance (MR) brain image sequences. We present justification fo...
Yue Wang, Tülay Adali, Chi-Ming Lau, Sun-Yuan...
ICIP
2010
IEEE
13 years 5 months ago
Saliency detection using maximum symmetric surround
Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. Recently, full-resolution salient ma...
Radhakrishna Achanta, Sabine Süsstrunk
CIVR
2007
Springer
157views Image Analysis» more  CIVR 2007»
14 years 2 months ago
Using multiple segmentations for image auto-annotation
Automatic image annotation techniques that try to identify the objects in images usually need the images to be segmented first, especially when specifically annotating image reg...
Jiayu Tang, Paul H. Lewis