On reducing the size of structured meshes with a novel video object extraction algorithm

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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Novel tracking-based moving object extraction algorithm

Journal of Electronic Imaging ◽

10.1117/1.1482095 ◽

2002 ◽

Vol 11 (3) ◽

pp. 393 ◽

Cited By ~ 1

Author(s):

Jianping Fan ◽

Essam A. El-Kwae ◽

Mohand-Said Hacid ◽

Feng Liang

Keyword(s):

Moving Object ◽

Object Extraction ◽

Extraction Algorithm

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Video object extraction using optimized smoothed dirichlet process multi-view learning with improved adaptive modified Markova random field

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.17610 ◽

2018 ◽

Vol 7 (4) ◽

pp. 2598

Author(s):

G S. Gowri ◽

Dr. P. Ponmuthuramalingam

Keyword(s):

Random Field ◽

Dirichlet Process ◽

Video Segmentation ◽

Target Object ◽

Object Extraction ◽

Contour Tracking ◽

Video Object ◽

Object Boundary ◽

Current Frame ◽

Film Making

Video object extraction (VOE) using segmentation from a video sequence is a very important task in editing and multimedia analysis for film making. Most of the VOE approaches required prior knowledge about background and foreground to extract target objects. In this paper, an Optimized smoothed Dirichlet Process Multi-view learning with improved adaptive Modified Markov Random Field which is enhanced by adaptive shape prior modified graph cut (OsDPMVL-IASMMRF) model has been extended for video-based object extraction. The contour tracking has been additionally included OsDPMVL-IASMMRF for VOE. The Teh–Chin algorithm has been used with OsDPMVL-IASMMRF for predicting the contour in the current frame by matching the extracted object contour from the previous segmented frame. The contour tracking propagates the shape of the target object, whereas the OsDPMVL-IASMMRF segmentation refined the object boundary and the shape for enhancing the accuracy of video segmentation. The experimental outcomes show that the proposed approach provides better segmentation results in terms of accuracy, precision and recall.

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Research on TV Goniometer Object Extraction Algorithm Based on Threshold Segmentation

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.889-890.1093 ◽

2014 ◽

Vol 889-890 ◽

pp. 1093-1098

Author(s):

He Chen ◽

Nan Li ◽

Tian Chen Huang ◽

Rong Xia Duan

Keyword(s):

Optimal Algorithm ◽

Detection System ◽

Detection Algorithm ◽

Field Of View ◽

Object Extraction ◽

Gray Level ◽

Line Extraction ◽

Standard Signal ◽

Extraction Algorithm ◽

Target Extraction

In the TV goniometer detection system, to play the signal and field of view points line extraction is a key link in the process of parameter detection. Combination of target processing requirements, this article will target extraction algorithm based on gray level threshold and edge detection algorithm is studied, and through the experimental analysis to select the optimal algorithm was applied to the detection of TV goniometer; According to the characteristics of the standard signal and view points, lines, and put forward the corresponding methods of target recognition, and is verified through experiments

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