Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project

The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system

POPRAWA METOD KOMPENSACJI RUCHU PORUSZAJĄCYCH SIĘ OBIEKTÓW DYNAMICZNYCH W STREAMIE WIDEO SYSTEMU WIDEOKONFERENCYJNEGO

Videoconferencing gives us the opportunity to work and communicate in real time, as well as to use collective applications, interactive information exchange. Videoconferencing systems are one of the basic components of the organization of manegment, ensuring, the timeliness and necessary quality management of the implementation of objective control over the solution of the tasks. The quality of the image and the time of transmission of video information is unsatisfactory for the quality control of the troops. Considered ways to increase the efficiency of management and operational activities, due to methods of compensation of motion, using technology to reduce the volume of video data for quality improvement.Wideokonferencje dają możliwość pracy i komunikowania się w czasie rzeczywistym, a także korzystania ze zbiorowych aplikacji, interaktywnej wymiany informacji. Systemy wideokonferencyjne są jednym z podstawowych elementów organizacji zarządzania, zapewniając terminowość i niezbędne zarządzanie jakością w zakresie realizacji kontroli nad rozwiązaniem zadań. Jakość obrazu i czas transmisji informacji wideo jest niezadowalający dla kontroli jakości wojsk. Rozważono sposoby zwiększania efektywności zarządzania i działań operacyjnych, ze względu na metody kompensacji ruchu, z wykorzystaniem technologii zmniejszającej ilość danych wideo w celu poprawy jakości

Region and object segmentation algorithms in the Qimera segmentation platform

In this paper we present the Qimera segmentation platform and describe the different approaches to segmentation that have been implemented in the system to date. Analysis techniques have been implemented for both region-based and object-based segmentation. The region-based segmentation algorithms include: a colour segmentation algorithm based on a modified Recursive Shortest Spanning Tree (RSST) approach, an implementation of a colour image segmentation algorithm based on the K-Means-with-Connectivity-Constraint (KMCC) algorithm and an approach based on the Expectation Maximization (EM) algorithm applied in a 6D colour/texture space. A semi-automatic approach to object segmentation that uses the modified RSST approach is outlined. An automatic object segmentation approach via snake propagation within a level-set framework is also described. Illustrative segmentation results are presented in all cases. Plans for future research within the Qimera project are also discussed

Realtime object extraction and tracking with an active camera using image mosaics

[[abstract]]Moving object extraction plays a key role in applications such as object-based videoconference, surveillance, and so on. The dimculties of moving object segmentation lie in the fact that physical objects are normally not homogeneous with to low-level features and it's usually tough to segment them accnrately and efficiently. Object segmentation based on prestored background information has proved to be effective and efficient in several applications such as videophone, video conferencing, and surveillance, etc. The previous works, however, were mainly concentrated on object segmentation with a static camera and in a stationary background. In this paper, we propose a robust and fast segmentation algorithm and a reliable tracking strategy without knowing the shape of the object in advance. The proposed system can real-time extract the foreground from the background and track the moving object with an active (pan-tilt) camera such that the moving object always stays around the center of images.[[fileno]]2030144030033[[department]]電機工程學

Video object transmission by means of virtual reality based object extraction

Abstract This paper presents a new technique to extract objects from a real complex background so that a video sequence can be decomposed into a set of objects as required for object oriented video compression techniques. The proposed method is based on a background subtraction technique. However, instead of using a fixed background, the system relies on predicting one from a previously constructed virtual model of the environment. Thus, camera movements are allowed. These movements are estimated by means of a tracker device. We also present the virtual model construction technique for indoor environments. The method has been successfully tested for several different video sequences including capture errors, partially mapped virtual environments and camera positioning errors. Further work will focus on extending the virtual models not only to environment, but also to objects, and integrating the method in a MPEG4 standard compression system

Recognizing Falls from Silhouettes

A major problem among the elderly involves falling. The recognition of falls from video first requires the segmentation of the individual from the background. To ensure privacy, segmentation should result in a silhouette that is a binary map indicating only the body position of the individual in an image. We have previously demonstrated a segmentation method based on color that can recognize the silhouette and detect and remove shadows. After the silhouettes are obtained, we extract features and train hidden Markov models to recognize future performances of these known activities. In this paper, we present preliminary results that demonstrate the usefulness of this approach for distinguishing between a few common activities, specifically with fall detection in mind.The authors were partially supported by NSF ITR grant IIS-0428420 and the U.S. Administration on Aging, under grant 90AM3013

Adaptive Silhouette Extraction In Dynamic Environments Using Fuzzy Logic

Extracting a human silhouette from an image is the enabling step for many high-level vision processing tasks, such as human tracking and activity analysis. In a previous paper, we addressed some of the challenges in silhouette extraction and human tracking in a real-world unconstrained environment where the background is complex and dynamic. We extracted features from image regions, accumulated the feature information over time, fused high-level knowledge with low-level features, and built a time-varying background model. A problem with our system is that by adapting the background model, objects moved by a human are difficult to handle. In order to reinsert them into the background, we run the risk of cutting off part of the human silhouette, such as in a quick arm movement. In this paper, we develop a fuzzy logic inference system to detach the silhouette of a moving object from the human body. Our experimental results demonstrate that the fuzzy inference system is very efficient and robust.The authors are grateful for the support from NSF ITR grant IIS-0428420 and the U.S. Administration on Aging, under grant 90AM3013

A Hierarchical Segmentation Algorithm for Face Analysis. Application to Lipreading

International audienceA hierarchical algorithm for face analysis is presented in this paper. A color video sequence of speaker's face is acquired, under natural lighting conditions and without any particular make-up. The application aims at providing geometrical features of the face for scalable video transmission when no specific model of the speaker face is assumed. First, a logarithmic hue transform is performed from RGB to HI (hue, intensity) color space. Next, a Markov random field modeling regularizes motion and hue information within a spatiotemporal neighborhood. The hierarchical segmentation labels the different areas of the face. Results are shown on the lower part of the face and compared with standard color segmentation algorithm (fuzzy c-means). A speaker's lip shape with inner and outer borders is extracted from the final labeling and used to initialize an active contours stage