'Video sequences' diaporamas de présentation

Muhammad Saleem Koul, SM IEEE mskoul@uta EE Dept., UT Arlington

Muhammad Saleem Koul, SM IEEE mskoul@uta.edu EE Dept., UT Arlington. EE 5359: Multimedia Processing Final Project. Error Resilience and Performance Evaluation of H.264/AVC video streams in a Lossy Wireless Environment. Synopsis.

527 views • 37 slides

Muhammad Saleem Koul, SM IEEE mskoul@uta EE Dept., UT Arlington

Muhammad Saleem Koul, SM IEEE mskoul@uta.edu EE Dept., UT Arlington. EE 5359: Multimedia Processing Final Project. Error Resilience and Performance Evaluation of H.264/AVC video streams in a Lossy Wireless Environment. Synopsis.

509 views • 37 slides

A Brief Overview of Computer Vision

A Brief Overview of Computer Vision. Jinxiang Chai. What is Computer Vision?. Computer vision is the science and technology of machines that see. Concerned with the theory for building artificial systems that obtain information from images.

541 views • 36 slides

Outline

Measuring Interaction QoE in Internet Videoconferencing Prasad Calyam (Presenter) Ohio Supercomputer Center, The Ohio State University Mark Haffner, Prof. Eylem Ekici Prof. Chang-Gun Lee The Ohio State University Seoul National University MMNS, November 1 st 2007. Outline.

491 views • 33 slides

PROPERTY OF PIMA COUNTY JTED, 2010

Multimedia/Audio Visual. 1. PROPERTY OF PIMA COUNTY JTED, 2010. BELLWORK. Have you ever noticed why some digital images look better than others? Write down three reasons about what makes some images better than others. After you have finished answering the question, share with your partner.

265 views • 26 slides

A System for Night Video Acquisition and Synchronisation

342 views • 24 slides

292 views • 21 slides

A ? -domain Rate Controller for Multiplexed Video Sequences

301 views • 19 slides

Xin Li LDCSEE, WVU Email: xin.li@ieee

365 views • 19 slides

Compressive Sensing Techniques for Video Acquisition

Compressive Sensing Techniques for Video Acquisition. EE5359 Multimedia Processing December 8,2009 Madhu P. Krishnan. Contents. Introduction to Image Acquisition Problem Statement Compressive Sensing Concept System Results Conclusion References. Introduction to Image Acquisition.

369 views • 18 slides

ETISEO Project

ETISEO Project. Ground Truth & Video annotation. ETISEO - GT. For each video sequence, the evaluator will generate the corresponding GT: - Using the Viper-GT Annotation tool ( U Maryland ). Video sequences are characterized considering: - day time : day, sunrise, nightfall, night

311 views • 18 slides

Visual Odometry David Nister, CVPR 2004

Visual Odometry David Nister, CVPR 2004. 2005. 1. 4 Computer Vision Lab. Young Ki Baik. Contents. Introduction Algorithm Experimental results Conclusion and opinion. Introduction. Visual Odometry Usage of visual information as a sensor

1.1k views • 16 slides

Chirag Jain, Sriram Sethuraman Ittiam Systems (Pvt.) Ltd., Bangalore, India

A LOW-COMPLEXITY, MOTION-ROBUST, SPATIO-TEMPORALLY ADAPTIVE VIDEO DE-NOISER WITH IN-LOOP NOISE ESTIMATION. Chirag Jain, Sriram Sethuraman Ittiam Systems (Pvt.) Ltd., Bangalore, India Image Processing, 2008. ICIP. Outline. Introduction Proposed Algorithm LLMMSE based spatial filtering

230 views • 16 slides

Information Directorate Air Force Research Laboratory

Information Directorate Air Force Research Laboratory. SPIE Annual Meeting 2002. Field Tests of Error-Resilient 3-D SPIHT vs. MPEG-2. Experimental Results. Sungdae Cho Keesook J. Han William A. Pearlman Bruce W. Suter. Center for Integrated Transmission and Exploitation (CITE).

198 views • 12 slides

Information Directorate Air Force Research Laboratory

Information Directorate Air Force Research Laboratory. SPIE Annual Meeting 2002. Field Tests of Error-Resilient 3-D SPIHT vs. MPEG-2. Experimental Results. Sungdae Cho Keesook J. Han William A. Pearlman Bruce W. Suter. Center for Integrated Transmission and Exploitation (CITE).

180 views • 12 slides

Information Directorate Air Force Research Laboratory

Information Directorate Air Force Research Laboratory. SPIE Annual Meeting 2002. Field Tests of Error-Resilient 3-D SPIHT vs. MPEG-2. Experimental Results. Sungdae Cho Keesook J. Han William A. Pearlman Bruce W. Suter. Center for Integrated Transmission and Exploitation (CITE).

190 views • 12 slides

In collaboration with: Computer Vision Group Indexing Video Sequences

In collaboration with: Computer Vision Group Indexing Video Sequences. Low level features in video sequences. Goal: Indexing Video repositories based on the low level features. Color (Red, Green, Yellow, Blue) Orientation (0 degree, 45 deg, 90 deg, 135 deg) Intensity (High, Low)

228 views • 11 slides

Dictionary-based Face Recognition from Video ECCV 2012

239 views • 9 slides

204 views • 9 slides

Visual Saliency Detection

Visual Saliency Detection. REU Student: LaTia Jefferson Graduate Student: Nasim Souly. Visual Salience. Definition Background research Human visual system General saliency Orientation (scanning process) Bottom-up versus top-down Importance

503 views • 5 slides