Block-based Motion Estimation in Video Frames using Artificial Neural Networks: A Selective Review | Zendy

Krishna Kumar | Zendy; Krishan Kumar | Zendy; Rahul Kumar Mishra | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Block-based Motion Estimation in Video Frames using Artificial Neural Networks: A Selective Review

Author(s) -

Krishna Kumar,

Krishan Kumar,

Rahul Kumar Mishra

Publication year - 2016

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2016908668

Subject(s) - computer science , block (permutation group theory) , artificial neural network , motion estimation , motion (physics) , artificial intelligence , estimation , computer vision , machine learning , pattern recognition (psychology) , mathematics , geometry , management , economics

Nowadays, we are very frequently transmitting the video over internet. This is due to an extensive increase in multimedia applications over hand held devices, such as smart mobile phones and also other advance conventional devices. Motion Estimation is an important field of study in the area of motion analysis and motion compression. The motion estimation is done by using two basic approaches, namely, pixel-based motion estimation and block-based motion estimation. Here we have proposed a detailed study literature survey and review of the block-based estimation methods in detail. This paper presents a comprehensive review of block based motion estimation techniques which plays a vital role in multimedia transmission over public network. The advantage of this review paper is to find the absolute optimal solution.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research