Structural motion estimation via Hilbert transform enhanced phase-based video processing

2022 ◽  
Vol 166 ◽  
pp. 108418
Author(s):  
G. Liu ◽  
M.Z. Li ◽  
Z. Mao ◽  
Q.S. Yang
Keyword(s):  
Motion Estimation ◽  
Hilbert Transform ◽  
Video Processing ◽  
Structural Motion

Correlation Based Rood Pattern Search (CBRPS) for Motion Estimation in Video Processing

2019 ◽  
Vol 36 (6) ◽  
pp. 5989-5999
Author(s):  
Hussain Ahmed Choudhury ◽  
Nidul Sinha ◽  
Monjul Saikia
Keyword(s):  
Motion Estimation ◽  
Video Processing ◽  
Pattern Search

Algorithm and Architecture for Adaptive Motion Estimation in Video Processing

2013 ◽  
Vol 30 (1) ◽  
pp. 24 ◽  
Author(s):  
Anand Paul ◽  
K Bharanitharan ◽  
JiaJi Wu
Keyword(s):  
Motion Estimation ◽  
Video Processing ◽  
Adaptive Motion

High Performance VLSI Design of Diamond Search Algorithm for Fast Motion Estimation

2016 ◽  
Vol 25 (09) ◽  
pp. 1650114
Author(s):  
Rohan Mukherjee ◽  
Vikrant Mahajan ◽  
Anindya Sundar Dhar ◽  
Indrajit Chakrabarti
Keyword(s):  
Motion Estimation ◽  
Video Processing ◽  
Search Algorithm ◽  
Critical Path ◽  
Video Codec ◽  
Path Delay ◽  
Hardware Complexity ◽  
Search Technique ◽  
Fast Motion Estimation ◽  
Diamond Search

Motion estimation (ME) accounts for the major part of computational complexity of any video coding standard. The diamond search (DS) algorithm is widely used as a fast search technique to perform motion estimation. In this paper, a novel architecture for the diamond search technique is proposed that efficiently handles memory addressing and reduces hardware complexity. The proposed architecture meets the speed requirements for real-time video processing without compromising the area. The design when implemented in Verilog HDL on Virtex-5 technology and synthesized using Xilinx ISE Design Suite 12.4, gives rise to a critical path delay of 3.25 ns and the equivalent area is calculated to be 3.5[Formula: see text]K gate equivalent. Working at a frequency of 308 MHz, the proposed design can process 128 CIF frames per second. So, the proposed architecture can be incorporated in a video codec targeted for commercial devices like smart-phones, camcorders and video conferencing system.

scholarly journals Advances in Motion Detection and Tracking of Human as a Target

2019 ◽  
Vol 8 (11) ◽  
pp. 3470-3473
Keyword(s):  
Motion Estimation ◽  
Video Compression ◽  
Video Processing ◽  
Image Data ◽  
Image Sequences ◽  
Stereo Correspondence ◽  
Image Domain ◽  
Motion Patterns ◽  
Estimation Algorithms ◽  
Detection And Tracking

Motion estimation of a target is the major area with higher computational complexity in video processing. It is the progression of discovery the motion patterns that describe the transformation from one frame to another in a sequence of video. Therefore, it is reasonable to carry out motion estimation only where movement is present. Image data in an image series remains mostly the same between frames along the target motion. To make use of the image statistics redundancy in image sequences, there is a need to guess motion. Motion estimation is valid for video compression improvement, stereo correspondence, object tracking and finding optical flow. Many precise methods have been proposed in the framework of one or more of these applications. Most motion estimation algorithms either operate directly in the image domain or finding the similar metric that measures how alike two pixels or two patches of pixels. In this paper, a review of a variety of motion estimation technique is presented

Sign in / Sign up

Export Citation Format

Share Document