Current increasing effort of broadcast providers to transmit UHD (Ultra High Definition) content is likely to increase demand for ultra high definition televisions (UHDTVs). To compress UHDTV content, several alternat...
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ISBN:
(纸本)9781628412444
Current increasing effort of broadcast providers to transmit UHD (Ultra High Definition) content is likely to increase demand for ultra high definition televisions (UHDTVs). To compress UHDTV content, several alternative encoding mechanisms exist. In addition to internationally recognized standards, open access proprietary options, such as VP9 video encoding scheme, have recently appeared and are gaining popularity. One of the main goals of these encoders is to efficiently compress video sequences beyond HDTV resolution for various scenarios, such as broadcasting or internet streaming. In this paper, a broadcast scenario rate-distortion performance analysis and mutual comparison of one of the latest video coding standards H.265/HEVC with recently released proprietary video coding scheme VP9 is presented. Also, currently one of the most popular and widely spread encoder H.264/AVC has been included into the evaluation to serve as a comparison baseline. The comparison is performed by means of subjective evaluations showing actual differences between encoding algorithms in terms of perceived quality. The results indicate a dominance of HEVC based encoding algorithm in comparison to other alternatives if a wide range of bit-rates from very low to high bit-rates corresponding to low quality up to transparent quality when compared to original and uncompressed video is considered. In addition, VP9 shows competitive results for synthetic content and bit-rates that correspond to operating points for transparent or close to transparent quality video.
The advances of ubiquitous communication infrastructures, the rapid adoption of mobile devices and pervasive computing technologies has allowed e-learning users access to multimedia learning contents in e-learning env...
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The advances of ubiquitous communication infrastructures, the rapid adoption of mobile devices and pervasive computing technologies has allowed e-learning users access to multimedia learning contents in e-learning environments. However, because of the diversity and heterogeneity of the mobile users, their preferences, and the rich multimedia learning content, it is a major challenge for the access of learning content by the desired devices in the e-learning environment to user's satisfaction in terms of QoS demands. In order to alleviate the challenge of learning content mismatch, content adaptation is essential. To this end, we propose an ACO-based multimediacontent adaptation approach, which inherits the adoption of ACO-based path selection behavior in the path computation for appropriate learning content customization. We compare our proposed approach with other two competitive algorithms, measure the performance and find that our proposed algorithms outperforms the basic AntNet and Genetic in terms of success rate, latency, runtime comparison and convergence. The performance evaluations are conducted using NetLogo simulation environment.
The advent of the digital television in Brazil has allowed users to access interactive channels. Once interactive channels are available, the users are able to find multimediacontent such as movies and breaking news ...
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The advent of the digital television in Brazil has allowed users to access interactive channels. Once interactive channels are available, the users are able to find multimediacontent such as movies and breaking news programs, to send and/or receive emails, to access interactive applications and also other contents. In this context, a high demand of requests from users is expected. Therefore, from the content provider's point of view, the determination of transmission parameters is needed in order to ensure the best quality of transmission to every user. The aforementioned identification problem is modelled as an optimization problem and a solution procedure based on metaheuristic techniques is proposed. Genetic Algorithm and Tabu Search metaheuristics are employed separately and coupled in a hybrid scheme to define the best transmission policy, optimizing the transmission parameters, such as audio and video transmission rates. Based on the experimental results, the hybrid algorithm has produced better solutions which meet the quality requirements.
In the era of big data, the use of formal models and techniques to represent and manage information is a necessary task to implement efficient intelligent information systems. In this paper we propose a complete frame...
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In the era of big data, the use of formal models and techniques to represent and manage information is a necessary task to implement efficient intelligent information systems. In this paper we propose a complete framework to annotate and categorize images. Our approach is based on multimedia ontologies organized following a formal model to represent knowledge. Our ontologies use multimedia data and linguistic properties to bridge the gap between the target semantic classes and the available low-level multimedia descriptors. The multimedia features are automatically extracted using algorithms based on MPEG-7 standard. The informative image content is annotated with semantic information extracted from our ontologies and the categories are dynamically built by means of a general knowledge base. Experimental results show the efficiency of our approach in the annotation and classification tasks using a combination of textual and visual components.
Our society is creating, storing and using an ever increasing volumes of digital multimediacontent. We have access to hundreds of billions of images and videos on the Internet, in the archives of professional content...
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ISBN:
(纸本)9781479976874
Our society is creating, storing and using an ever increasing volumes of digital multimediacontent. We have access to hundreds of billions of images and videos on the Internet, in the archives of professional content creators and owners, and in the personal libraries of home users. In this context, content-based identification of images' and videos and visual search capabilities are essential enablers for a range of applications that require fast, robust and efficient algorithms. The interoperability of the technologies and systems is also an important consideration. During the lecture Miroslaw Bober will review the latest advances in content fingerprinting and visual search and how they impact related standardisation efforts within the MPEG group. In particular will present the MPEG Visual Signatures, which include the Image Signature and Video Signature content description tools. The Visual Signatures are designed specifically to enable fast and robust identification of near duplicate or derived (modified) visual content in large-scale databases. We will also look at the latest addition to the MPEG family of standards: Compact Descriptors for Visual Search (CDVS). Achieving a state-of-the-art identification and recognition performance, the applications are numerous and include rights management and monetization, distribution management, usage monitoring, and professional or personal database management.
Future Internet is foreseen to fully handle a wide range of multimedia services allowing their access trough diverse computing devices such as laptops, TVs, PDAs and 3G mobile phones interconnected via different wire-...
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Future Internet is foreseen to fully handle a wide range of multimedia services allowing their access trough diverse computing devices such as laptops, TVs, PDAs and 3G mobile phones interconnected via different wire-line and wireless networking technologies. Such a diversification in the computational context reinforces the need of personalized and adaptive media services towards better end-user experience. However, building context-aware media systems raises a number of challenges related to (i) context representation, management and provisioning (ii) binding context situations to services and (iii) performing context-driven service and content adaptation; and this in a dynamic, scalable and interoperable way. In this paper, we present a future Internet architecture1 that enables automated situation-driven media services' discovery, composition and delivery. The proposed solution relies on a new Home-Box layer among which the context-awareness and adaptation features are distributed.
content inappropriate for children on Internet television is a serious problem in today's multimedia world. There are numerous methods which are used to control the content of the transmitted television programmes...
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ISBN:
(纸本)9781467344715
content inappropriate for children on Internet television is a serious problem in today's multimedia world. There are numerous methods which are used to control the content of the transmitted television programmes. However, these well-known methods do not solve the above mentioned problem completely. The paper presents a more effective method for automatic identification of the provider's logo based on an original image sequence analysis. The automatic identification of the provider's logo can be used to block access to video programmes of the selected providers. The method has been tested on some chosen video transmissions on-line, achieving over 98% of correct identification.
Successful music recommendation systems need to incorporate information on at least three levels: the music content, the music context, and the user context. The former refers to features derived from the audio signal...
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ISBN:
(纸本)9781450321068
Successful music recommendation systems need to incorporate information on at least three levels: the music content, the music context, and the user context. The former refers to features derived from the audio signal;the second refers to aspects of the music or artist not encoded in the audio, nevertheless important to human music perception;the third refers to contextual aspects of the user which change dynamically. In this paper, we briefly review the well-researched categories of music content and music context features, before focusing on user-centric models, which have been neglected for a long time in music retrieval and recommendation approaches. In particular, we address the following tasks: (i) geospatial music recommendation from microblog data, (ii) user-aware music playlist generation on smart phones, and (iii) matching places of interest and music. The approaches presented for task (i) rely on large-scale data inferred from microblogs, motivated by the fact that social media represent an unprecedented source of information about every topic of our daily lives. Information about music items and artists is thus found in abundance in user-generated data. The questions of how to infer information relevant to music recommendation from microblogs and what to learn from them are discussed. So are different ways of incorporating this kind of information into state-of-the-art music recommendation algorithms. The presented approaches targeted at tasks (ii) and (iii) model the user in a more comprehensive way than just using information about her location and music listening habits. We report results of a user study aiming at investigating the relationship between music listening activity and a large set of contextual user features. Based on these, an intelligent mobile music player that automatically adapts the current playlist to the user context is presented. Eventually, we discuss different methods to solve task (iii), i.e., to determine music that suits a gi
Present day mobile phones have evolved as multimedia devices, where users can capture and store photos, videos on their mobile phones. As the amount of digital multimediacontent expands, it becomes increasingly diffi...
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Present day mobile phones have evolved as multimedia devices, where users can capture and store photos, videos on their mobile phones. As the amount of digital multimediacontent expands, it becomes increasingly difficult to find specific images in the device, giving rise to problems of organization, storing and retrieval of images. To improve human access to a large unstructured data in their personal collections on mobile phones, there is a need for effective and precise retrieval algorithms for the user to search browse and interact with these collections in real time. Retrieval algorithms are highly complex and this characteristic becomes more intense on mobile platform due to restrictions in architecture and computing power. In this paper we propose a speech based image retrieval algorithm for personal collections optimized for porting on to a mobile phones. We have treated the speech spectrogram as an image and applied trace transformation to obtain an unique and robust identifier string that acts as a fingerprint for image retrieval systems. Trace transform is popular in image processing algorithms because it is robust to affine transforms for feature extraction. The proposed algorithm exhibits optimization in memory and retrieval time costs.
In this work we propose a novel approach to automatically detect a swimmer and estimate his/her pose continuously in order to derive an estimate of his/her stroke rate given that we observe the swimmer from the side. ...
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ISBN:
(纸本)9780819489517
In this work we propose a novel approach to automatically detect a swimmer and estimate his/her pose continuously in order to derive an estimate of his/her stroke rate given that we observe the swimmer from the side. We divide a swimming cycle of each stroke into several intervals. Each interval represents a pose of the stroke. We use specifically trained object detectors to detect each pose of a stroke within a video and count the number of occurrences per time unit of the most distinctive poses (so-called key poses) of a stroke to continuously infer the stroke rate. We extensively evaluate the overall performance and the influence of the selected poses for all swimming styles on a data set consisting of a variety of swimmers.
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