Multimedia Information Retrieval and Multimedia Data Mining Chengcui Zhang Assistant Professor Dept. of Computer and Information Science University of.

Slides:

Advertisements

Similar presentations

Kien A. Hua Division of Computer Science University of Central Florida.

Advertisements

Automatic Video Shot Detection from MPEG Bit Stream Jianping Fan Department of Computer Science University of North Carolina at Charlotte Charlotte, NC.

Automated Shot Boundary Detection in VIRS DJ Park Computer Science Department The University of Iowa.

Prof. Carolina Ruiz Computer Science Department Bioinformatics and Computational Biology Program WPI WELCOME TO BCB4003/CS4803 BCB503/CS583 BIOLOGICAL.

Multimedia Semantic Web and MPEG-7 Ana B. Benitez ee.columbia.edu Image and Advanced Television Lab (ADVENT) Department of Electrical Engineering.

Visual Event Detection & Recognition Filiz Bunyak Ersoy, Ph.D. student Smart Engineering Systems Lab.

Data Mining Techniques Cluster Analysis Induction Neural Networks OLAP Data Visualization.

Data warehouse example

1 Texmex – November 15 th, 2005 Strategy for the future Global goal “Understand” (= structure…) TV and other MM documents Prepare these documents for applications.

1 Content-Based Retrieval (CBR) -in multimedia systems Presented by: Chao Cai Date: March 28, 2006 C SC 561.

Content-based Video Indexing, Classification & Retrieval Presented by HOI, Chu Hong Nov. 27, 2002.

Semantic Web and Web Mining: Networking with Industry and Academia İsmail Hakkı Toroslu IST EVENT 2006.

Recent Developments in Human Motion Analysis

Object-based Image Representation Dr. B.S. Manjunath Sitaram Bhagavathy Shawn Newsam Baris Sumengen Vision Research Lab University of California, Santa.

Multimedia Search and Retrieval Presented by: Reza Aghaee For Multimedia Course(CMPT820) Simon Fraser University March.2005 Shih-Fu Chang, Qian Huang,

Content-Based Image Retrieval (CBIR) Student: Mihaela David Professor: Michael Eckmann Most of the database images in this presentation are from the Annotated.

Vigilant Real-time storage and intelligent retrieval of visual surveillance data Dr Graeme A. Jones.

Architecture & Data Management of XML-Based Digital Video Library System Jacky C.K. Ma Michael R. Lyu.

Databases and Data Mining

ECE160 Spring 2009Lecture 201 ECE160 / CMPS182 Multimedia Lecture 20: Spring 2009 Image Recognition and Retrieval.

Visual Information Retrieval Chapter 1 Introduction Alberto Del Bimbo Dipartimento di Sistemi e Informatica Universita di Firenze Firenze, Italy.

MS I Multimedia Databases Arif Ghafoor Professor Electrical and Computer Engineering Purdue University.

University of Kansas The Intelligent Systems & Information Management Laboratory Costas Tsatsoulis, Director.

Advanced Database Applications Database Indexing and Data Mining CS591-G1 -- Fall 2001 George Kollios Boston University.

Dan Schonfeld Co-Director, Multimedia Communications Laboratory Professor, Departments of ECE, CS & Bioengineering University of Illinois at Chicago.

OLAM and Data Mining: Concepts and Techniques. Introduction Data explosion problem: –Automated data collection tools and mature database technology lead.

Introduction to ECE432 Instructor: Ying Wu Dept. Electrical & Computer Engr. Northwestern University Evanston, IL 60208

Intelligent Database Systems Lab 國立雲林科技大學 National Yunlin University of Science and Technology Mining Rare and Frequent Events in Multi-camera Surveillance.

Petr Chmelař UIFS UIFS Seminar Thesis Objectives OLAM SE Publications Teaching 1 / 9 2 nd Year Summary Report Supervisor Doc. Ing. Jaroslav Zendulka, CSc.

Multimedia Databases (MMDB)

Unsupervised Learning-Based Spatio-Temporal Vehicle Tracking and Indexing for Transportation Multimedia Database Systems Chengcui Zhang Department of Computer.

Motion Object Segmentation, Recognition and Tracking Huiqiong Chen; Yun Zhang; Derek Rivait Faculty of Computer Science Dalhousie University.

A Proposal for a Video Modeling for Composing Multimedia Document Cécile ROISIN - Tien TRAN_THUONG - Lionel VILLARD Presented by: Tien TRAN THUONG Project.

Dept. of Electrical Engineering and Computer Science, Northwestern University Context-Aware Optimization of Continuous Query Maintenance for Trajectories.

Event-Based Fusion of Distributed Multimedia Data Sources Vincent Oria Department of Computer Science New Jersey Institute of Technology Newark, NJ

Object Based Processing for Privacy Protected Surveillance Karl Martin Kostas N. Plataniotis University of Toronto Dept. of Electrical and Computer Engineering.

Data Mining By Dave Maung.

ImArray - An Automated High-Performance Microarray Scanner Software for Microarray Image Analysis, Data Management and Knowledge Mining Wei-Bang Chen and.

Efficient Visual Object Tracking with Online Nearest Neighbor Classifier Many slides adapt from Steve Gu.

CS332 Visual Processing Department of Computer Science Wellesley College CS 332 Visual Processing in Computer and Biological Vision Systems Overview of.

March 31, 1998NSF IDM 98, Group F1 Group F Multi-modal Issues, Systems and Applications.

1 Applications of video-content analysis and retrieval IEEE Multimedia Magazine 2002 JUL-SEP Reporter: 林浩棟.

Data and Applications Security Developments and Directions Dr. Bhavani Thuraisingham The University of Texas at Dallas Lecture #15 Secure Multimedia Data.

Contact : Bernadette Bouchon-Meunier, Patrick Gallinari, Jean-Gabriel Ganascia LIP6, UPMC, 8 rue du Capitaine Scott, Paris, France

Search Engine using Web Mining COMS E Web Enhanced Information Mgmt Prof. Gail Kaiser Presented By: Rupal Shah (UNI: rrs2146)

Mining real world data Multi media data mining. Multimedia Data Mining Multimedia data types –any type of information medium that can be represented,

Semantic Extraction and Semantics-Based Annotation and Retrieval for Video Databases Authors: Yan Liu & Fei Li Department of Computer Science Columbia.

Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas Cyber Security Research on Engineering Solutions Dr. Bhavani.

MULTIMEDIA DATA MODELS AND AUTHORING

Relevance Feedback in Image Retrieval System: A Survey Tao Huang Lin Luo Chengcui Zhang.

  Computer vision is a field that includes methods for acquiring,prcessing, analyzing, and understanding images and, in general, high-dimensional data.

By Akhilesh K. Sinha Nishant Singh Supervised by Prof. Amitabha Mukerjee Video Surveillance of Basketball Matches and Goal Detection Indian Institute of.

Smart Web Search Agents Data Search Engines >> Information Search Agents - Traditional searching on the Web is done using one of the following three: -

3D Motion Classification Partial Image Retrieval and Download Multimedia Project Multimedia and Network Lab, Department of Computer Science.

MULTIMEDIA SYSTEMS CBIR & CBVR. Schedule Image Annotation (CBIR) Image Annotation (CBIR) Video Annotation (CBVR) Video Annotation (CBVR) Few Project Ideas.

TRECVID IES Lab. Intelligent E-commerce Systems Lab. 1 Presented by: Thay Setha 05-Jul-2012.

Data Mining - Introduction Compiled By: Umair Yaqub Lecturer Govt. Murray College Sialkot.

Digital Video Library - Jacky Ma.

Visual Information Retrieval

Datamining : Refers to extracting or mining knowledge from large amounts of data Applications : Market Analysis Fraud Detection Customer Retention Production.

Color-Texture Analysis for Content-Based Image Retrieval

CSE/EE 576 Computer Vision Spring 2007

CSEP 576 Computer Vision Winter 2008

Introduction What IS computer vision?

Data Warehousing and Data Mining

CSE/EE 576 Computer Vision Spring 2010

Web Mining Department of Computer Science and Engg.

Example of Event-Based Video Data (Touch-down Scenario)

Presentation transcript:

Multimedia Information Retrieval and Multimedia Data Mining Chengcui Zhang Assistant Professor Dept. of Computer and Information Science University of Alabama at Birmingham

General Content-Based Image Retrieval (CBIR)

Object-Based Image Retrieval Example – Query by two objects Techniques used: Image segmentation Neural network Multiple instance learning …

Research Issues … Multiple object retrieval for image databases Learning of composite model Information fusion Apply the developed techniques to other applications such as drug activity discovery, pattern recognition for medical image analysis, etc.

Video Data Mining Example: Locate the interesting events (goals, corner kicks, etc.) in a large amount of raw, unprocessed soccer videos Facilitate automatic annotation and indexing of the high-level structures of soccer videos Soccer videos …… Corner kick eventGoal event ……

Research Issues … Video event mining: Detect other types of soccer events like free kicks, referees, and fouls, etc. Discover the underlying associations among different events/subevents Develop a scalable soccer video database system and a flexible user query interface Apply to other types of videos (TV news, Basketball, etc.)

A Soccer Video Retrieval System Using Temporal Relationships

Video Surveillance for Intelligent Transportation Systems (ITS) Frame 132 Frame 138 Frame 142

Video Surveillance for Intelligent Transportation Systems (ITS) Vehicle tracking sequence …

Research Issues … Handle vehicle object overlapping Vehicle classification (car, SUV, truck, etc.) Spatio-temporal modeling of vehicle trajectories to enable efficient query of traffic surveillance data and to support modeling and analysis of behavior- based traffic phenomena such as car-truck interaction.

Other Research Projects Microarray image analysis …