Automatic moving object extraction algorithm using histogram mapping and local watershed techniques for shadow effect

2007 ◽  
Author(s):  
Hong-Yeon Yu ◽  
Min-Sung Kim ◽  
Do-Young Jun ◽  
Chang-Hyun Kim ◽  
Sung Hoon Hong
Keyword(s):  
Moving Object ◽  
Object Extraction ◽  
Shadow Effect ◽  
Extraction Algorithm

Novel tracking-based moving object extraction algorithm

2002 ◽  
Vol 11 (3) ◽  
pp. 393 ◽  
Author(s):  
Jianping Fan ◽  
Essam A. El-Kwae ◽  
Mohand-Said Hacid ◽  
Feng Liang
Keyword(s):  
Moving Object ◽  
Object Extraction ◽  
Extraction Algorithm

scholarly journals Exclusive Block Matching for Moving Object Extraction and Tracking

2010 ◽  
Vol E93-D (5) ◽  
pp. 1263-1271 ◽  
Author(s):  
Zhu LI ◽  
Kenichi YABUTA ◽  
Hitoshi KITAZAWA
Keyword(s):  
Block Matching ◽  
Moving Object ◽  
Object Extraction

A Hybrid Model for Emotion Detection from Text

2017 ◽  
Vol 7 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Samar Fathy ◽  
Nahla El-Haggar ◽  
Mohamed H. Haggag
Keyword(s):  
Semantic Similarity ◽  
Hybrid Model ◽  
Semantic Analysis ◽  
Main Idea ◽  
Object Extraction ◽  
Emotion Detection ◽  
Suggested Approach ◽  
Matching Process ◽  
Extraction Algorithm ◽  
Input Sentence

Emotions can be judged by a combination of cues such as speech facial expressions and actions. Emotions are also articulated by text. This paper shows a new hybrid model for detecting emotion from text which depends on ontology with keywords semantic similarity. The text labelled with one of the six basic Ekman emotion categories. The main idea is to extract ontology from input sentences and match it with the ontology base which created from simple ontologies and the emotion of each ontology. The ontology extracted from the input sentence by using a triplet (subject, predicate, and object) extraction algorithm, then the ontology matching process is applied with the ontology base. After that the emotion of the input sentence is the emotion of the ontology which it matches with the highest score of matching. If the extracted ontology doesn't match with any ontology from the ontology base, then the keyword semantic similarity approach used. The suggested approach depends on the meaning of each sentence, the syntax and semantic analysis of the context.

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