Detection and Identification of Rare Audio-visual Cues PDF Download
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Author: Daphna Weinshall
Publisher: Springer Science & Business Media
ISBN: 364224033X
Category : Computers
Languages : en
Pages : 186
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Book Description
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to estimate the current state of the world. An implied assumption is that the future is stochastically similar to the past. The approach fails when the system encounters situations that are not anticipated from the past experience. In contrast, successful natural organisms identify new unanticipated stimuli and situations and frequently generate appropriate responses. The observation described above lead to the initiation of the DIRAC EC project in 2006. In 2010 a workshop was held, aimed to bring together researchers and students from different disciplines in order to present and discuss new approaches for identifying and reacting to unexpected events in information-rich environments. This book includes a summary of the achievements of the DIRAC project in chapter 1, and a collection of the papers presented in this workshop in the remaining parts.
Author: Daphna Weinshall
Publisher: Springer Science & Business Media
ISBN: 364224033X
Category : Computers
Languages : en
Pages : 186
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Book Description
Machine learning builds models of the world using training data from the application domain and prior knowledge about the problem. The models are later applied to future data in order to estimate the current state of the world. An implied assumption is that the future is stochastically similar to the past. The approach fails when the system encounters situations that are not anticipated from the past experience. In contrast, successful natural organisms identify new unanticipated stimuli and situations and frequently generate appropriate responses. The observation described above lead to the initiation of the DIRAC EC project in 2006. In 2010 a workshop was held, aimed to bring together researchers and students from different disciplines in order to present and discuss new approaches for identifying and reacting to unexpected events in information-rich environments. This book includes a summary of the achievements of the DIRAC project in chapter 1, and a collection of the papers presented in this workshop in the remaining parts.
Author: Markus Vincze
Publisher: Springer Science & Business Media
ISBN: 3540795464
Category : Computers
Languages : en
Pages : 560
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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Computer Vision Systems, ICVS 2008, held in Santorini, Greece, May 12-15, 2008. The 23 revised papers presented together with 30 poster presentations and 2 invited papers were carefully reviewed and selected from 128 submissions. The papers are organized in topical sections on cognitive vision, monitor and surveillance, computer vision architectures, calibration and registration object recognition and tracking, learning, human machine interaction as well as cross modal systems.
Author: Stefanos Kollias
Publisher: Springer Science & Business Media
ISBN: 3540386254
Category : Artificial intelligence
Languages : en
Pages : 1041
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Book Description
Author: Petr Sojka
Publisher: Springer Science & Business Media
ISBN: 3540873902
Category : Computers
Languages : en
Pages : 663
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Book Description
This book constitutes the refereed proceedings of the 11th International Conference on Text, Speech and Dialogue, TSD 2008, held in Brno, Czech Republic, September 8-12, 2008. The 79 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 173 submissions. The topics of the conference include, but are not limited to, text corpora and tagging; transcription problems in spoken corpora; sense disambiguation; links between text and speech oriented systems; parsing issues; parsing problems in spoken texts; multi-lingual issues; multi-lingual dialogue systems; information retrieval and information extraction; text/topic summarization; machine translation; semantic networks and ontologies; semantic web; speech modeling; speech segmentation; speech recognition; search in speech for IR and IE; text-to-speech synthesis; dialogue systems; development of dialogue strategies; prosody in dialogues; emotions and personality modeling; user modeling; knowledge representation in relation to dialogue systems; assistive technologies based on speech and dialogue; applied systems and software; facial animation; and visual speech synthesis
Author: Xiaodan Zhuang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Audio-visual event detection aims to identify semantically defined events that reveal human activities. Most previous literature focused on restricted highlight events, and depended on highly ad-hoc detectors for these events. This research emphasizes generalizable robust modeling of single-microphone audio cues and/or single-camera visual cues for the detection of real-world events, requiring no expensive annotation other than the known timestamps of the training events. To model the audio cues for event detection, we leverage statistical models proven effective in speech recognition. First, a tandem connectionist-HMM approach combines the sequence modeling capabilities of the hidden Markov model (HMM) with the context-dependent discriminative capabilities of an artificial neural network. Second, an SVM-GMM-supervector approach uses noise-robust kernels to approximate the KL divergence between feature distributions in different audio segments. The proposed methods outperform our top-ranked HMM-based acoustic event detection system in the CLEAR 2007 Evaluation, which detects twelve general meeting room events such as keyboard typing, cough and chair moving. To model the visual cues, we propose the Gaussianized vector representation, constructed by adapting a set of Gaussian mixtures according to the set of patch-based descriptors in an image or video clip, regularized by the global Gaussian mixture model. The innovative visual modeling approach establishes unsupervised correspondence between local descriptors in different images or video clips, and achieves outstanding performance in a video event categorization task on ten LSCOM-defined events in the Trecvid broadcast news data, such as exiting car, running and people marching. Following an efficient branch-and-bound search scheme, we further propose an object localization approach for the Gaussianized vector representation. We jointly model audio and visual cues for improved event detection using multi-stream HMMs and coupled HMMs (CHMM). Spatial pyramid histograms based on the optical flow are proposed as a generalizable visual representation that does not require training on labeled video data. In a multimedia meeting room non-speech event detection task, the proposed methods outperform previously reported systems leveraging ad-hoc visual object detectors and sound localization information obtained from multiple microphones.
Author: Kristen Murphy
Publisher:
ISBN:
Category :
Languages : en
Pages : 152
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Book Description
Author: Hugo Bertolotti
Publisher:
ISBN: 9781124546186
Category : Auditory perception
Languages : en
Pages : 126
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Book Description
Abstract: This study attempted to resolve the findings within Vu et al. and Bertolotti and Strybel regarding horizontal and vertical auditory cue displacement on target identification by examining local target area visual saliency and target uncertainty. Targets were identified with either an auditory cue or auditory-visual cue. Auditory cues were noise bursts spatially coincident with, or directionally displaced 40 or 80 from the target. Visual cues (circle: 6.50 radius) accurately identified the local target area surrounding the target. Target uncertainty varied the percentage of targets present within a given session. For auditory cues, as target probability increased, horizontal auditory cue displacement became a greater detriment to target identification regardless of error magnitude. For auditory-visual cues, while both target present and absent search times decreased significantly compared to auditory cues, target absent identification demonstrated the most significant improvement from increasing local target area visual saliency. Design recommendations and future research are discussed.
Author: Elyse S Sussman
Publisher: Frontiers E-books
ISBN: 2889193713
Category : Auditory pathways
Languages : en
Pages : 152
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Book Description
In natural environments, the auditory system is typically confronted with a mixture of sounds originating from different sound sources. As sounds spread over time, the auditory system has to continuously decompose competing sounds into distinct meaningful auditory objects or “auditory streams” referring to certain sound sources. This decomposition work, which was termed by Albert Bregman as “Auditory scene analysis” (ASA), involves two kinds of grouping to be done. Grouping based on simultaneous cues, such as harmonicity and on sequential cues, such as similarity in acoustic features over time. Understanding how the brain solves these tasks is a fundamental challenge facing auditory scientist. In recent years, the topic of ASA was broadly investigated in different fields of auditory research, including a wide range of methods, studies in different species, and modeling. Despite the advance in understanding ASA, it still proves to be a major challenge for auditory research. This includes verifying whether experimental findings are transferable to more realistic auditory scenes. A central approach in understanding ASA is the use of certain stimulus parameters that produce an ambiguous percept. The advantage of such an approach is that different perceptual organizations can be studied without varying physical stimulus parameters. Additionally, the perception of ambiguous stimuli can be volitionally controlled by intention or task. By using this one can mirror real hearing situations where listeners intent to identify and to localize auditory sources. Recently it was also found that in classical auditory streaming sequences perceptual ambiguity was not restricted to but was observed over a broad range of stimulus parameters. The proposed Research Topic pursues to bring together scientist in the different fields of auditory research whose work addresses the issue of perceptual ambiguity. Researchers were welcome to contribute experimental reports, computational modeling, and reviews that consider auditory ambiguity in its modality specific characteristics as well as in comparison to visual ambiguous figures. The overall goal of contributions was to consider the experimental findings from the perspective of real auditory scenes. In a broader sense, the Research Topic was open for contributions which are related to the issue of active listening in complex scenes.
Author: Cheng-Lin Liu
Publisher: Springer
ISBN: 3319496859
Category : Computers
Languages : en
Pages : 379
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Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Brain Inspired Cognitive Systems, BICS 2016, held in Beijing, China, in November 2016. The 32 full papers presented were carefully reviewed and selected from 43 submissions. They discuss the emerging areas and challenges, present the state of the art of brain-inspired cognitive systems research and applications in diverse fields by covering many topics in brain inspired cognitive systems related research including biologically inspired systems, cognitive neuroscience, models consciousness, and neural computation.
Author:
Publisher:
ISBN:
Category : Neurology
Languages : en
Pages : 640
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Book Description
