'Motion estimation' presentation slideshows

Motion and Stereo

Motion and Stereo. EE4H, M.Sc 0407191 Computer Vision Dr. Mike Spann m.spann@bham.ac.uk http://www.eee.bham.ac.uk/spannm. Introduction.

1.11k views • 101 slides

By: Yair Weiss and Edward H. Adelson. Presenting: Ady Ecker and Max Chvalevsky.

EM for Motion Segmentation. By: Yair Weiss and Edward H. Adelson. Presenting: Ady Ecker and Max Chvalevsky. .

1.06k views • 72 slides

Complexity reduction in VP6 to H.264 transcoder using motion vector (MV) reuse

Complexity reduction in VP6 to H.264 transcoder using motion vector (MV) reuse. Jay R Padia Electrical Engineering Graduate Student The University of Texas at Arlington Supervising Professor Dr. K. R. Rao. Contents. Introduction VP6 H.264 VP6 & H.264 comparison Cascaded architecture

611 views • 51 slides

Trends in CMOS Image Sensor Technology and Design

Trends in CMOS Image Sensor Technology and Design. Abbas El Gamal Department of Electrical Engineering Stanford University. CCD Image Sensors. High QE and low dark current Serial readout: Slow readout Complex clocking and supply requirements High power consumption

1.21k views • 50 slides

CPUs

CPUs. Input and output. Supervisor mode, exceptions, traps. Co-processors. I/O devices. Usually includes some non-digital component. Typical digital interface to CPU:. status reg. CPU. mechanism. data reg. Application: 8251 UART.

649 views • 48 slides

Introduction to video coding

564 views • 41 slides

Efficient Real-Time Multicore Image Processing on TI C66x final presentation

Efficient Real-Time Multicore Image Processing on TI C66x final presentation. Yaron Doweck Yael Einziger Supervisor: Mike Sumszyk Spring 2011 Semester Project. Learn to use the new TI C6678 multi-core platform and to exploit its abilities and advantages.

544 views • 38 slides

Image Quality Assessment: From Error Visibility to Structural Similarity

Image Quality Assessment: From Error Visibility to Structural Similarity. Zhou Wang. Motivation. original Image. MSE=0, MSSIM=1. MSE=225, MSSIM=0.949. MSE=225, MSSIM=0.989. MSE=215, MSSIM=0.671. MSE=225, MSSIM=0.688. MSE=225, MSSIM=0.723. Perceptual Image Processing.

671 views • 36 slides

Windows Media Video 9

Windows Media Video 9. Tarun Bhatia tarun79_us@yahoo.com Multimedia Processing Lab University Of Texas at Arlington 11/05/04. Introduction 1. Introduction 2. Introduction 3.

414 views • 27 slides

Nowcasting of thunderstorms from GOES Infrared and Visible Imagery

Nowcasting of thunderstorms from GOES Infrared and Visible Imagery. Valliappa.Lakshmanan@noaa.gov Bob.Rabin@noaa.gov National Severe Storms Laboratory & University of Oklahoma http://cimms.ou.edu/~lakshman/. Nowcasting Thunderstorms From Infrared and Visible Imagery.

361 views • 24 slides

Super-Resolution

660 views • 23 slides

Rate-Distortion Optimized Motion Estimation for Error Resilient Video Coding

Hua Yang and Kenneth Rose Signal Compression Lab ECE Department University of California Santa Barbara, USA Mar. 2005. Rate-Distortion Optimized Motion Estimation for Error Resilient Video Coding. Outline. Motion estimation (ME) for coding efficiency Conventional ME

394 views • 23 slides

285 views • 18 slides

Research Topic

Research Topic. Error Concealment Techniques in H.264/AVC for Wireless Video Transmission. Vineeth Shetty Kolkeri EE Graduate,UTA. Purpose of H.264 / MPEG-4 part 10 Higher coding efficiency than previous standards, MPEG-1,2,4 part 2, H.261, H.263 2. Simple syntax specifications

298 views • 17 slides

Video Communication Final Project =Motion Estimation=

Video Communication Final Project =Motion Estimation=. Instructor : Chia -Hung Yeh Student : Po- jiun Lin (Neil) Date : 2011.1.13. Introduction. Motion Estimation is an important issue in any video processing system, especially in the video compression.

330 views • 17 slides

Motion estimation with tagged ultrasound images

250 views • 13 slides

Motion Estimation Final Project

Motion Estimation Final Project. Adviser: ??? Presenter: ???. Outline. Introduction Proposed motion estimation Comparison Demo conclusion. Introduction. Motion is continue and need more than 2 frames to display The motion vector in previous frame is very close to current frame.

448 views • 12 slides

Line Matching

Line Matching. Jonghee Park GIST CV-Lab. Introduction. Lines Fundamental feature in many computer vision fields 3D reconstruction, SLAM, motion estimation Useful features in low-textured and man-made structure Stereo Technology Assume that depth discontinuity mainly occurs nearby edges

284 views • 11 slides

Vision Based Automated Cluster Tester

Vision Based Automated Cluster Tester.

208 views • 8 slides

An enhanced estimation: motion and rotation estimation

An enhanced estimation: motion and rotation estimation. SHAN-HSIANG SHEN. Motivation. Video encoding methods such as H.264 and MPEG use motion estimation to increase compression rate. Paste each blocks from some reference frame to create current frame.

245 views • 7 slides