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Marcel Worring received the MSc degree (honors) and PhD degree, both in computer science, from the Vrije Universiteit, Amsterdam, The Netherlands, in 1988 and the University of Amsterdam in 1993, respectively. He is currently an associate professor at the University of Amsterdam. His interests are in multimedia search and systems. He is leading the MediaMill team which has been succesful in the last...
Steffen Staab is professor for databases and information systems at the University of Koblenz-Landau, leading the research group on Information Systems and Semantic Web (ISWeb). His interests lie in researching core technology for ontologies and semantic web as well as in applied research for exploiting these technologies for knowledge management,multimedia and software technology.He has participated...
A lot of texts are associated with Web images, such as image file name, ALT texts, surrounding texts etc on the corresponding Web pages. It is well known that the semantics of Web images are well correlated with these associated texts, and thus they can be used to infer the semantics of Web images. However, different types of associated texts may play different roles in deriving the semantics of Web...
The SenseCam is a wearable camera that automatically takes photos of the wearer’s activities, generating thousands of images per day. Automatically organising these images for efficient search and retrieval is a challenging task, but can be simplified by providing semantic information with each photo, such as the wearer’s location during capture time. We propose a method for automatically determining...
Attention is a psychological measurement of human reflection against stimulus. We propose a general framework of highlight detection by comparing attention intensity during the watching of sports videos. Three steps are involved: adaptive selection on salient features, unified attention estimation and highlight identification. Adaptive selection computes feature correlation to decide an...
This paper proposes a method for integrating player trajectories tracked in wide-angle images and identities by face and back-number recognition from images by a motion-controlled camera. In order to recover from tracking failures efficiently, the motion-controlled camera scans and follows players who are judged likely to undergo heavy occlusions several seconds in the future. The candidates of identities...
Direct encryption for the JPEG2000 code-streams by using a conventional block cipher needs an additional processing time, whereas the joint compression and encryption schemes increase the coding efficiency but with some sacrifices in security. In this paper, a Dually Randomized MQ coder (DRMQ) is presented to support both compression and encryption functionalities, and to achieve tradeoff between...
Speech intelligibility is the very essence of communications. When high noise can degrade a speech signal to the threshold of intelligibility, for example in mobile and military applications, introducing further degradation by a speech coder could prove critical. This paper investigates concepts towards a new speech coder that draws upon the field of image processing in a new multimedia approach....
The Active Appearance Models [1] and the derived Active Models (AM) [4] allow to robustly track the face of a single user that was previously learnt, but works poorly with multiple or unknown users. Our research aims at improving the tracking robustness by learning from video databases. In this paper, we study the relation between the face texture and the parameter gradient matrix, and propose a statistical...
Rate Distortion Optimization based spatial intra coding is a new feature of H.264/AVC standard. It efficiently improves the video coding performance by brutally utilizing variable block sizes and multiple prediction modes. Thus, extremely high computation complexity is required. This paper proposes a hybrid decision algorithm which can reduce unimportant block sizes and prediction modes. Entropy feature...
In this paper, we propose a new low complexity video compression method based on detecting blocks containing moving edges using only DCT coefficients. The detection, whilst being very efficient, also allows efficient motion estimation by constraining the search process to moving macro-blocks only. The encoders PSNR is degraded by 2dB compared to H.264/AVC inter for such scenarios, whilst requiring...
An efficient method that estimates the depth map of a 3D scene using the motion information of its H.264-encoded 2D video is presented. Our proposed method employs a revised version of the motion information. This is obtained based on the characteristics of the 3D human visual perception. The low complexity of our approach and its compatibility with future broadcasting networks allow its real-time...
Commercial blocks provide no extra value for video indexing, retrieval, archiving, or summarization of TV broadcasts. Therefore, automatic detection of commercial blocks is an important topic in the domain of multimedia information systems. We present a commercial detection approach which is based on logo detection performed in the compressed domain. The novelty of our approach is that by taking advantage...
In this paper, we propose a compression scheme for animated semi-regular meshes. This scheme includes a spatio-temporal wavelet filtering to exploit the coherence both in time and space. In order to optimize the quantization of both spatial and temporal wavelet coefficients, the proposed compression scheme also includes a model-based bit allocation. The experimental results show that this approach...
In the JPEG2000 standard the very cost intensive EBCOT encoder based on an arithmetic encoder with an embedded quantization is said to be the optimum. Embedded systems with limited processing power have difficulties to encode images into this JPEG2000 image format due to its high processing load. A rekursive optimization of the quantization is not possible. This paper proposes a new method based on...
Motivated by the impressive performance of cost-based scheduling for media streaming, we investigate its effectiveness in detail and analyze opportunities for further tunings and enhancements. Guided by this analysis, we propose a highly efficient enhancement technique that optimizes the scheduling decisions to increase the number of requests serviced concurrently and enhance user-perceived quality-of-service...
The Internet has been experiencing a large growth of the multimedia traffic of applications performing over an RTP stack implemented on top of UDP/IP. Since UDP does not offer a congestion control mechanism (unlikely TCP), studies on the rate control schemes have been increasingly done. Usually, new proposes are evaluated, by simulation, in terms of criteria such as fairness towards competing TCP...
Learning-based ranking is a promising approach to a variety of search tasks, which is aimed at automatically creating the ranking model based on training samples and machine learning techniques. However, the problem of lacking training samples labeled with relevancy degree or ranking orders is frequently encountered. To address this problem, we propose a novel graph-based learning to rank (GLRank)...
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