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Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipa-tory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service(More)
As amounts of publicly available video data grow, the need to automatically infer semantics from raw video data becomes significant. In this paper, we focus on the use of Dynamic Bayesian Networks (DBNs) for that purpose, and demonstrate how they can be effectively applied for fusing the evidence obtained from different media information sources. The
We propose LicenseScript as a new multiset rewrit-ing/logic based language for expressing dynamic conditions of use of digital assets such as music, video or private data. LicenseScript differs from other DRM languages in that it caters for the intentional but legal manipulation of data. We believe this feature is the answer to providing the flexibility(More)
This paper addresses content-based video retrieval with an emphasis on recognizing events in tennis game videos. In particular, we aim at recognizing different classes of tennis strokes using automatic learning capability of Hidden Markov Models. Driven by our domain knowledge, a robust player segmentation algorithm is developed for real video data.(More)
In a ciphertext-policy attribute-based encryption (CP-ABE) scheme, the data is encrypted under an access policy defined by a user who encrypts the data and a user secret key is associated with a set of attributes which identify the user. A user can decrypt the ciphertext if and only if his attributes satisfy the access policy. In CP-ABE, since the user(More)
As amounts of publicly available video data grow, the need to query this data efficiently becomes significant. Consequently, content-based retrieval of video data turns out to be a challenging and important problem. In this paper, we address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video(More)
When outsourcing data to an untrusted database server, the data should be encrypted. When using thin clients or low-bandwidth networks it is best to perform most of the work at the server. In this paper we present a method, inspired by secure multi-party computation, to search efficiently in encrypted data. XML elements are translated to polynomials. A(More)
Schema matching attempts to discover semantic map-pings between elements of two schemas. Elements are cross compared using various heuristics (e.g., name, data-type, and structure similarity). Seen from a broader perspective , the schema matching problem is a combinatorial problem with an exponential complexity. This makes the naive matching algorithms for(More)
This paper introduces a new approach for specifying transaction management requirements for workflow applications. We propose independent models for the specification of workflow and transaction properties. Although we distinguish multiple transaction properties in our approach, we focus on atomicity in this paper. We propose an intuitive notation to(More)