Comparison of prediction schemes with motion information reuse for low complexity spatial scalability

2005 ◽  
Author(s):  
Koen De Wolf ◽  
Robbie De Sutter ◽  
Wesley De Neve ◽  
Rik Van de Walle
Keyword(s):  
Low Complexity ◽  
Motion Information ◽  
Information Reuse

Retrieving Human Action by Fusing the Motion Information of Interest Points

2018 ◽  
Vol 27 (03) ◽  
pp. 1850008 ◽  
Author(s):  
Mohsen Ramezani ◽  
Farzin Yaghmaee
Keyword(s):  
Video Retrieval ◽  
State Of The Art ◽  
Low Complexity ◽  
Human Action ◽  
Local Features ◽  
The Internet ◽  
Motion Information ◽  
Interest Points ◽  
Representation Method ◽  
Human Action Retrieval

In response to the fast propagation of videos on the Internet, Content-Based Video Retrieval (CBVR) was introduced to help users find their desired items. Since most videos concern humans, human action retrieval was introduced as a new topic in CBVR. Most human action retrieval methods represent an action by extracting and describing its local features as more reliable than global ones; however, these methods are complex and not very accurate. In this paper, a low-complexity representation method that more accurately describes extracted local features is proposed. In this method, each video is represented independently from other videos. To this end, the motion information of each extracted feature is described by the directions and sizes of its movements. In this system, the correspondence between the directions and sizes of the movements is used to compare videos. Finally, videos that correspond best with the query video are delivered to the user. Experimental results illustrate that this method can outperform state-of-the-art methods.

scholarly journals Machine learning-based H.264/AVC to HEVC transcoding via motion information reuse and coding mode similarity analysis

2019 ◽  
Vol 13 (1) ◽  
pp. 34-43 ◽  
Author(s):  
Hongwei Lin ◽  
Xiaohai He ◽  
Linbo Qing ◽  
Shan Su ◽  
Shuhua Xiong
Keyword(s):  
Machine Learning ◽  
Similarity Analysis ◽  
Motion Information ◽  
Information Reuse ◽  
Coding Mode

Visual Tracking of an Object with its Motion Information

2009 ◽  
Vol 129 (5) ◽  
pp. 977-984
Author(s):  
Atsutoshi Shimeno ◽  
Seiichi Uchida ◽  
Ryo Kurazume ◽  
Rin-ichiro Taniguchi ◽  
Tsutomu Hasegawa
Keyword(s):  
Visual Tracking ◽  
Motion Information
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