Trip Report for The IASTED International Conference on Internet and Multimedia Systems and Applications (EuroIMSA 2006) February 13-15, 2006 Innsbruck,

Trip Report for

The IASTED International Conference on

Internet and Multimedia Systems and Applications (EuroIMSA 2006)

February 13-15, 2006Innsbruck, Austria

Bob Kinicki

Euro IMSA February 13-15, 20062

General Observations• My Opinion: the conference was weak, but

there were a few interesting ideas.• There were few American authors.• The International flavor of the conference

was quite strong.• The conference did give a sense of

Europe’s future research directions.• Goal: To glean new thoughts from a few

papers.

Euro IMSA February 13-15, 20063

A Ubiquitous Zoo Guide

Euro IMSA February 13-15, 20064

A System level Integration for Remote Learning Services based on DVB-T

Platform

Euro IMSA February 13-15, 20065

A System level Integration for Remote Learning Services based on DVB-T

Platform

Image FeatureDetection

FeatureTracking

Camera MotionAnalysis

Overview

Video SourceAutomatic extraction of camera motion

Applications: Video Indexing Video Retrieval Scene Analysis

MetadataGeneration

Extract the image features using Harris corner detector

Track the image features along a shot using basic tracker based on translational image motion model

Determine the camera motion by analyzing the motion trajectories of image features

Image FeatureDetection

FeatureTracking

Camera MotionAnalysis

•A Sense of Speed in Camera Motion

Euro IMSA February 13-15, 20067

A Sense of Speed in Camera Motion

Euro IMSA February 13-15, 20068

A Sense of Speed in Camera Motion

Euro IMSA February 13-15, 20069

Conclusions

• The camera motion and speed are determined by analyzing the motion trajectories of image features along an image sequence.

• Based on the experimental results, the speed can be converted into three levels of motion that can be perceived by human (i.e., slow, medium, and fast). This helps to facilitate the motion annotation and content description of a video particularly in the applications of video retrieval, indexing and scene analysis.

Euro IMSA February 13-15, 200610

Plenary Session: Gabriele Kotsis

“Beyond Desktop Computing”

• A talk about future multimedia applications for cooperative work.

• Department of Telecooperation at Linz, Austria

• Pervasive, ubiquitous computing

• Embedding IT in Objects

Euro IMSA February 13-15, 200611

Plenary Session: Gabriele Kotsis

“Beyond Desktop Computing”

• Spiffy interfaces, e.g., in glasses• Mirror TV• I/O brush• Interested in the sociology and psychology

aspects of multimedia interfaces.• “From the sage on the stage to the guide on the

side”• Everyone is becoming producers of video.• Must use care not to exclude people (e.g. color

blindness).

Euro IMSA February 13-15, 200612

Euro IMSA February 13-15, 200613

Exaggeration of Extremely Detailed 3D Faces

Euro IMSA February 13-15, 200614

Impact of Uncompressed Video Transmissions on

Network Quality of Service Parameters

Euro IMSA February 13-15, 200615

Impact of Uncompressed Video Transmissions on

Network Quality of Service Parameters

Euro IMSA February 13-15, 200616

Impact of Uncompressed Video Transmissions on

Network Quality of Service Parameters

Euro IMSA February 13-15, 200617

Impact of Uncompressed Video Transmissions on

Network Quality of Service Parameters

Euro IMSA February 13-15, 200618

On Improving Performance for IEEE 802.11 Wireless LANs under Congested and Error-

Prone Environments

Euro IMSA February 13-15, 200619

Scene-Level Analysis for Tennis Sports Video using Weighted Linear Combination of

Visual Cues

Euro IMSA February 13-15, 200620

Automatic Sports Video

Analysis using Audio Clues and

Context Knowledge

Euro IMSA February 13-15, 200621

A Video Classification Method using User Perceptive Video Quality

Euro IMSA February 13-15, 200622

A Video Classification Method using User Perceptive Video Quality

Euro IMSA February 13-15, 200623

A Video Classification Method using User Perceptive Video Quality

Euro IMSA February 13-15, 200624

A Video Classification Method using User Perceptive Video Quality