Video sequence feature extraction and segmentation using likelihood regression model

2021 ◽  
Author(s):  
B. Satheesh Kumar ◽  
K. Seetharaman
Keyword(s):  
Feature Extraction ◽  
Regression Model ◽  
Video Sequence ◽  
Sequence Feature

Research on the Harris Algorithm of Feature Extraction for Moving Targets in the Video

2015 ◽  
Vol 741 ◽  
pp. 378-381
Author(s):  
Jun Yan ◽  
Yan Piao
Keyword(s):  
Feature Extraction ◽  
Video Sequence ◽  
Threshold Value ◽  
Moving Targets ◽  
Rapid Acquisition ◽  
Central Pixel ◽  
Extraction Algorithm ◽  
Detection Window ◽  
Feature Information ◽  
The Difference

This paper studies a problem which is the rapid acquisition feature information of moving targets in a video sequence. Selecting the harris algorithm as a feature extraction algorithm, but harris algorithm has a problem of running slowly .Opting 3 * 3 window as the detection window, analyzing the similarity between the window capacity pixel and central pixel, then using the difference to measure this similarity of pixels, when the difference is greater than the set threshold value, we thought they are different, otherwise they are similar.After that characteristics of regional screening was completed. The target areas were divided into feature areas and non-feature regions, but we only calculated the response functions of characteristic areas. The algorithm’s executing efficiency improved.

scholarly journals Runoff sequence feature extraction and prediction using an enhanced sparse autoencoder

Authorea ◽  
2020 ◽  
Author(s):  
Lipeng Qian ◽  
LI Junfeng ◽  
Changzheng Liu ◽  
Junhong Tao ◽  
Fulong Chen
Keyword(s):  
Feature Extraction ◽  
Sequence Feature ◽  
Sparse Autoencoder
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