By Petros Maragos, Alexandros Potamianos, Patrick Gros
ISBN-10: 0387763155
ISBN-13: 9780387763156
ISBN-10: 0387763163
ISBN-13: 9780387763163
Multimodal Processing and interplay: Audio, Video and Text provides prime quality, state of the art learn rules and effects from theoretic, algorithmic and alertness viewpoints. This edited quantity includes either cutting-edge experiences and unique contributions by means of best specialists within the clinical and technological box of multimedia. It grew out of a four-year collaboration between learn teams partaking within the eu community of Excellence on Multimedia figuring out, Semantics, Computation and studying (MUSCLE).
Multimodal Processing and interplay: Audio, Video and Text covers a vast spectrum of novel views, analytic instruments, algorithms, layout practices and functions in multimedia technology and engineering with emphasis on multimodal integration and modality fusion. This quantity additionally includes contributions within the quarter of interplay with multimedia, particularly multimodal interfaces for having access to multimedia content.
Multimodal Processing and interplay: Audio, Video and Text is designed for a certified viewers composed of practitioners and researchers in and academia. This booklet is acceptable for advanced-level scholars in laptop technological know-how and engineering as well.
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Additional info for Multimodal Processing and Interaction: Audio, Video, Text
Sample text
When one touches one object while looking at another). Integration of Visual and Auditory Information for Spatial Localization There is ample evidence that the human brain integrates multiple sensory modalities to accomplish various inference tasks such as spatial localization. In general, this integration improves performance. However, it may also lead to illusionary perception phenomena such as the “ventriloquist effect”, where the movement of a dummy’s mouth alters the perceived location of the ventriloquist’s voice and hence creates a localization bias.
Finally, the posterior conditional distribution P (S|D) expresses the a posteriori probability of the audiovisual scene S after observing the data D. The posterior distribution is the main tool for Bayesian inference since it allows us to use the data as observations to update the estimate of S based on Bayes’ formula. This updating, applied to perception, agrees with cognitive psychology’s view that, as we move in the environment we sense the world and our sensations get mapped to percepts which are accompanied by degrees of belief; these percepts may change as we acquire new information.
This model is known as visual capture, because human perception is usually dominated by vision over hearing. A typical example is watching a film in a movie theater where the visual information comes from the screen whereas the auditory information (loudspeakers’ sound) originates from the sides, but human observers usually perceive the sound origin as coincident with the location of the visual stimulus. The other theory advocates for a linear integration of the two modalities through a weighted visual-auditory average, which corresponds to a weak fusion scheme [99, 583].