A growing percentage of the world population now uses image and video coding technologies on a regular basis. These technologies are behind the success and quick deployment of services and products such as digital pictures, digital television, DVDs, and Internet video communications. Today's digital video coding paradigm represented by the ITU-T and MPEG standards mainly relies on a hybrid of blockbased transform and interframe predictive coding approaches. In this coding framework, the encoder architecture has the task to exploit both the temporal and spatial redundancies present in the video sequence, which is a rather complex exercise. As a consequence, all standard video encoders have a much higher computational complexity than the decoder (typically five to ten times more complex), mainly due to the temporal correlation exploitation tools, notably the motion estimation process. This type of architecture is well-suited for applications where the video is encoded once and decoded many times, i.e., one-to-many topologies, such as broadcasting or video-on-demand, where the cost of the decoder is more critical than the cost of the encoder.Distributed source coding (DSC) has emerged as an enabling technology for sensor networks. It refers to the compression of correlated signals captured by
The objective of this paper is to show that for every color space there exists an optimum skin detector scheme such that the performance of all these skin detectors schemes is the same. To that end, a theoretical proof is provided and experiments are presented which show that the separability of the skin and no skin classes is independent of the color space chosen.
A common feature found in practically all technical approaches proposed for face recognition is the use of only the luminance information associated to the face image. One may wonder ifthis is due to the low importance of the color information in face recognition or due to other less technical reasons such as the no availability of color image database. Motivated by this reasoning, we have performed a variety of tests using a global eigen approach developed previously [I], which has been modfied to cope with the color information. Our results show that the use of the color information embedded in a eigen approach, can improve the recognition rate when compared to the same scheme which uses only the luminance information.
a b s t r a c tDistributed Video Coding (DVC) is a new video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. Recently, practical DVC solutions have been proposed with promising results; however, there is still a need to study in a more systematic way the set of application scenarios for which DVC may bring major advantages. This paper intends to contribute for the identification of the most DVC friendly application scenarios, highlighting the expected benefits and drawbacks for each studied scenario. This selection is based on a proposed methodology which involves the characterization and clustering of the applications according to their most relevant characteristics, and their matching with the main potential DVC benefits.
These results highlight the importance of taking into account the type of pain when assessing cognitive performance in CP patients and demonstrate the influence of the emotional state of the patient, especially if depression is present.
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