Proceedings. IEEE International Conference on Multimedia and Expo

This paper proposes an efficient method of segmenting noisy audio signals using a linear binary Walsh transform, when the signal components are closely spaced and the time intervals between adjacent signal components are unknown. It is shown that the Walsh transform is appropriate for segmenting a noisy waveform. A subset of the Walsh functions is chosen to cover principally the noise subspace such that the resulting linear combination of the selected basis functions captures the features that can discriminate between signal and noise. In the absence of a priori information about the signal and noise statistics, the proposed scheme is based on the linear combination of those basis functions which must be able to identify the adjacent signal components. It is not necessary that the basis functions reconstruct the noise-free versions of the signal components. The only restriction is that the segment length should be some integer power of 2 for the most accurate segmentation. The simulation examples show effectiveness in the segmentation of narrowly separated, noisy signals by using our simple segmentation method.

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In this paper, we present a fast motion estimation algorithm for arbitrarily shaped video coding in MPEG-4. This novel algorithm takes advantage of our new discovery about the close relation between the best matching block and its shape information-alpha plane. Without any additional padding computation, this new motion estimation algorithm computes the sum of absolute difference (SAD) between two alpha planes rather than the pixels' intensities. Compared with the full search block-matching algorithm (recommended in the MPEG-4 standard), the proposed algorithm achieves an impressive speed-up ratio with very minor quality degradation and little bit-count increase. Extensive simulations are provided in this paper to demonstrate this fact.

Interactive environments combine perception, action and communication to extend human-computer interaction. We believe that a fundamental challenge for interactive environments is developing models and methods for "context awareness". We present an ontology for context awareness for interactive environments. We show how the elements of this ontology correspond to the elements of a software architecture for observing situation and context. Within this framework, context predicts the evolution of the situation, and provides "meaning" for objects and events. Context also provides a specification for assembling federations of processes to measure properties, determine relations and detect events.

Synchronized Multimedia Integration Language (SMIL) 2.0 has a support for user interactions with its declarative event timing and temporal hyperlinking model. However, complex Web applications require more control over multimedia presentations. This is achieved with a support for a scripting language. The result is Dynamic SMIL, a combination of SMIL and a scripting language. We present the design and implementation of a player for Dynamic SMIL. It consists of a SMIL 2.0 player and a facility to run scripts with the help of XML Events. The SMIL player is also integrated into an XML browser, X-Smiles, thus enabling playing SMIL with XForms, XSL FO, SVG, and XHTML.

In MPEG-4, a video sequence can be divided into foreground object and background objects that are independently encoded. Using sprites can dramatically compress the overall bit rate, but not all video sequences can be so encoded. This paper introduces MPEG-4 multimode coding; it offers automatic coding mode decision, video object generation and high compression efficiency. The source video sequence is segmented and each segment is automatically categorized as either "normal", which is encoded using MPEG-4 simple profile, or as "sprite". Coding experiments show that if the bit rate is low, multimode coding offers higher coding efficiency than regular MPEG-4 in terms of frame rate and image quality.

In the course of work on the MPEG-7 standard, a binary format with special features for the encoding of XML data was required. These required key features are a high data compression ratio, provision for streaming, dynamic update of the document structure and fast random access of data entities in the compressed stream. To support these features, we propose a novel, schema-aware approach which exploits the knowledge of the standardized MPEG-7 syntax definition of the encoded XML document on the encoder and decoder side. The technique is part of the MPEG-7 standard. This paper gives an overview of the coding algorithm, including a comparison to standard (XML) compression tools.

We present a system for creating a photorealistic 3D face model of a specific person with a hierarchical structure for dynamic facial expression animation. The facial modeling procedure starts from the individual facial measurements which provides a highly accurate facial geometry and color information. Based on the reconstructed facial mesh, a deformable multi-layer soft tissue model is developed to simulate the dynamic behavior of the skin by taking into account its nonlinear stress-strain relationship. The underlying muscle and skull structure are physically modeled and integrated with the skin meshes. By taking as input a collection of reflectance images covering the face, the view-based texture blending method automatically generates a comprehensive texture map for photorealistic rendering. The resulting personalized face model with biomechanical structure is animated by numerically solving the governing dynamic equation. Using our system, we have synthesized realistic expressions on the authentic face model of a specific individual.

In last decade, we have seen the first steps to the end of passive television. Thanks to continuous advances in hardware and software, digital TV technology is now mature enough to enhance traditional TV sets (limited to content reproduction) with computing capability to run multimedia software integrating richer formats. A significant example of this progress is Internet access through television, which is becoming a reality in the last generation of digital set-top boxes. However, both media (computers and TVs) are different enough to require noteworthy modifications in their respective computing models. The MHP (multimedia home platform) standard is the first one that tries to define regulations in that sense. We comment on some technical aspects of the MHP solution.

Relevance feedback (RF) has become a powerful technique in content-based image retrieval. Most RF methods assume that positive images follow the single Gaussian distribution, which is not sufficient to model the actual distribution of images due to the gap between the semantic concept and low-level features. In this paper, the Gaussian mixture model (GMM) is applied to represent the distribution of positive images in relevance feedback, and a novel method is proposed to estimate the parameters of the GMM. Both positive and negative examples are used to estimate the number of Gaussian components. Furthermore, due to the lack of training samples, unlabeled data are also incorporated to estimate the covariance matrices. Experimental results show that our GMM-based RF method outperforms that based on a single Gaussian model.