Relevant bibliographies by topics / Visual scanpaths

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Visual scanpaths'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Visual scanpaths"

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Król, Michał, and Magdalena Ewa Król. "A Novel Eye Movement Data Transformation Technique that Preserves Temporal Information: A Demonstration in a Face Processing Task." Sensors 19, no. 10 (May 23, 2019): 2377. http://dx.doi.org/10.3390/s19102377.

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Existing research has shown that human eye-movement data conveys rich information about underlying mental processes, and that the latter may be inferred from the former. However, most related studies rely on spatial information about which different areas of visual stimuli were looked at, without considering the order in which this occurred. Although powerful algorithms for making pairwise comparisons between eye-movement sequences (scanpaths) exist, the problem is how to compare two groups of scanpaths, e.g., those registered with vs. without an experimental manipulation in place, rather than individual scanpaths. Here, we propose that the problem might be solved by projecting a scanpath similarity matrix, obtained via a pairwise comparison algorithm, to a lower-dimensional space (the comparison and dimensionality-reduction techniques we use are ScanMatch and t-SNE). The resulting distributions of low-dimensional vectors representing individual scanpaths can be statistically compared. To assess if the differences result from temporal scanpath features, we propose to statistically compare the cross-validated accuracies of two classifiers predicting group membership: (1) based exclusively on spatial metrics; (2) based additionally on the obtained scanpath representation vectors. To illustrate, we compare autistic vs. typically-developing individuals looking at human faces during a lab experiment and find significant differences in temporal scanpath features.
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Brandt, Stephan A., and Lawrence W. Stark. "Spontaneous Eye Movements During Visual Imagery Reflect the Content of the Visual Scene." Journal of Cognitive Neuroscience 9, no. 1 (January 1997): 27–38. http://dx.doi.org/10.1162/jocn.1997.9.1.27.

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In nine naïve subjects eye movements were recorded while subjects viewed and visualized four irregularly-checkered diagrams. Scanpaths, defined as repetitive sequences of fixations and saccades were found during visual imagery and viewing. Positions of fixations were distributed according to the spatial arrangement of subfeatures in the diagrams. For a particular imagined diagrammatic picture, eye movements were closely correlated with the eye movements recorded while viewing the same picture. Thus eye movements during imagery are not random but reflect the content of the visualized scene. The question is discussed whether scanpath eye movements play a significant functional role in the process of visual imagery.
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McClung, Sarah N., and Ziho Kang. "Characterization of Visual Scanning Patterns in Air Traffic Control." Computational Intelligence and Neuroscience 2016 (2016): 1–17. http://dx.doi.org/10.1155/2016/8343842.

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Characterization of air traffic controllers’ (ATCs’) visual scanning strategies is a challenging issue due to the dynamic movement of multiple aircraft and increasing complexity of scanpaths (order of eye fixations and saccades) over time. Additionally, terminologies and methods are lacking to accurately characterize the eye tracking data into simplified visual scanning strategies linguistically expressed by ATCs. As an intermediate step to automate the characterization classification process, we (1) defined and developed new concepts to systematically filter complex visual scanpaths into simpler and more manageable forms and (2) developed procedures to map visual scanpaths with linguistic inputs to reduce the human judgement bias during interrater agreement. The developed concepts and procedures were applied to investigating the visual scanpaths of expert ATCs using scenarios with different aircraft congestion levels. Furthermore, oculomotor trends were analyzed to identify the influence of aircraft congestion on scan time and number of comparisons among aircraft. The findings show that (1) the scanpaths filtered at the highest intensity led to more consistent mapping with the ATCs’ linguistic inputs, (2) the pattern classification occurrences differed between scenarios, and (3) increasing aircraft congestion caused increased scan times and aircraft pairwise comparisons. The results provide a foundation for better characterizing complex scanpaths in a dynamic task and automating the analysis process.
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Król, Magdalena Ewa, and Michał Król. "Scanpath similarity measure reveals not only a decreased social preference, but also an increased nonsocial preference in individuals with autism." Autism 24, no. 2 (July 27, 2019): 374–86. http://dx.doi.org/10.1177/1362361319865809.

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We compared scanpath similarity in response to repeated presentations of social and nonsocial images representing natural scenes in a sample of 30 participants with autism spectrum disorder and 32 matched typically developing individuals. We used scanpath similarity (calculated using ScanMatch) as a novel measure of attentional bias or preference, which constrains eye-movement patterns by directing attention to specific visual or semantic features of the image. We found that, compared with the control group, scanpath similarity of participants with autism was significantly higher in response to nonsocial images, and significantly lower in response to social images. Moreover, scanpaths of participants with autism were more similar to scanpaths of other participants with autism in response to nonsocial images, and less similar in response to social images. Finally, we also found that in response to nonsocial images, scanpath similarity of participants with autism did not decline with stimulus repetition to the same extent as in the control group, which suggests more perseverative attention in the autism spectrum disorder group. These results show a preferential fixation on certain elements of social stimuli in typically developing individuals compared with individuals with autism, and on certain elements of nonsocial stimuli in the autism spectrum disorder group, compared with the typically developing group.
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Gbadamosi, Joystone, and Wolfgang H. Zangemeister. "Visual Imagery in Hemianopic Patients." Journal of Cognitive Neuroscience 13, no. 7 (October 1, 2001): 855–66. http://dx.doi.org/10.1162/089892901753165782.

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In this article we report some findings about visual imagery in patients with stable homonymous hemianopia compared to healthy control subjects. These findings were obtained by analyzing the gaze control through recording of eye movements in different phases of viewing and imagery. We used six different visual stimuli for the consecutive viewing and imagery phases. With infrared oculography, we recorded eye movements during this presentation phase and in three subsequent imagery phases in absence of the stimulus. Analyzing the basic parameters of the gaze sequences (known as “scanpaths”), we discovered distinct characteristics of the “viewing scanpaths” and the “imagery scanpaths” in both groups, which suggests a reduced extent of the image within the cognitive representation. We applied different similarity measures (string/vector string editing, Markov analysis). We found a “progressive consistency of imagery,” shown through raising similarity values for the comparison of the late imagery scanpaths. This result suggests a strong top-down component in picture exploration: In both groups, healthy subjects and hemianopic patients, a mental model of the viewed picture must evolve very soon and substantially determine the eye movements. As our hemianopic patients showed analogous results to the normal subjects, we conclude that these patients are well adjusted to their deficit and, despite their perceptual defect, have a preserved cognitive representation, which follows the same top-down vision strategies in the process of visual imagery.
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Green, Melissa J., Leanne M. Williams, and Dean Davidson. "Visual scanpaths to threat-related faces in deluded schizophrenia." Psychiatry Research 119, no. 3 (August 2003): 271–85. http://dx.doi.org/10.1016/s0165-1781(03)00129-x.

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Wollstadt, Patricia, Martina Hasenjäger, and Christiane B. Wiebel-Herboth. "Quantifying the Predictability of Visual Scanpaths Using Active Information Storage." Entropy 23, no. 2 (January 29, 2021): 167. http://dx.doi.org/10.3390/e23020167.

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Entropy-based measures are an important tool for studying human gaze behavior under various conditions. In particular, gaze transition entropy (GTE) is a popular method to quantify the predictability of a visual scanpath as the entropy of transitions between fixations and has been shown to correlate with changes in task demand or changes in observer state. Measuring scanpath predictability is thus a promising approach to identifying viewers’ cognitive states in behavioral experiments or gaze-based applications. However, GTE does not account for temporal dependencies beyond two consecutive fixations and may thus underestimate the actual predictability of the current fixation given past gaze behavior. Instead, we propose to quantify scanpath predictability by estimating the active information storage (AIS), which can account for dependencies spanning multiple fixations. AIS is calculated as the mutual information between a processes’ multivariate past state and its next value. It is thus able to measure how much information a sequence of past fixations provides about the next fixation, hence covering a longer temporal horizon. Applying the proposed approach, we were able to distinguish between induced observer states based on estimated AIS, providing first evidence that AIS may be used in the inference of user states to improve human–machine interaction.
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Drusch, Gautier, and J. M. Christian Bastien. "Analyzing Web pages visual scanpaths: between and within tasks variability." Work 41 (2012): 1559–66. http://dx.doi.org/10.3233/wor-2012-0353-1559.

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Laeng, Bruno, and Dinu-Stefan Teodorescu. "Eye scanpaths during visual imagery reenact those of perception of the same visual scene." Cognitive Science 26, no. 2 (March 2002): 207–31. http://dx.doi.org/10.1207/s15516709cog2602_3.

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Boccignone, Giuseppe, and Mario Ferraro. "Feed and fly control of visual scanpaths for foveation image processing." annals of telecommunications - annales des télécommunications 68, no. 3-4 (July 18, 2012): 201–17. http://dx.doi.org/10.1007/s12243-012-0316-9.

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Dissertations / Theses on the topic "Visual scanpaths"

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Green, Melissa Jayne. "Facial affect processing in delusion-prone and deluded individuals: A continuum approach to the study of delusion formation." University of Sydney. Psychology, 2002. http://hdl.handle.net/2123/792.

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This thesis examines attentional and cognitive biases for particular facial expressions in delusion-prone and deluded individuals. The exploration of cognitive biases in delusion-prone individuals provides one means of elucidating psychological processes that might be involved in the genesis of delusions. Chapter 1 provides a brief review of the continuum approach to schizophrenia, and outlines recent theoretical conceptualisations of delusions. The study of schizophrenia phenomena at the symptom level has become a popular method of inquiry, given the heterogeneous phenotypic expression of schizophrenia, and the uncertainty surrounding the existence of a core neuropathology. Delusions are one of the most commonly experienced symptoms of schizophrenia, and have traditionally been regarded as fixed, false beliefs that are pathognomonic of an organic disease process. However, recent phenomenological evidence of delusional ideation in the general population has led to the conceptualisation of delusions as multi-dimensional entities, lying at the extreme end of a continuum from normal through to maladaptive beliefs. Recent investigations of the information processing abnormalities in deluded individuals are reviewed in Chapter 2. This strand of research has revealed evidence of various biases in social cognition, particularly in relation to threat-related material, in deluded individuals. These biases are evident in probabilistic reasoning, attribution style, and attention, but there has been relatively little investigation of cognitive aberrations in delusion-prone individuals. In the present thesis, social-cognitive biases were examined in relation to a standard series of faces that included threat-related (anger, fear) and non-threatening (happy, sad) expressions, in both delusion-prone and clinically deluded individuals. Chapters 3 and 4 present the results of behavioural (RT, affect recognition accuracy) and visual scanpath investigations in healthy participants assessed for level of delusion- proneness. The results indicate that delusion-prone individuals are slower at processing angry faces, and show a general (rather than emotion-specific) impairment in facial affect recognition, compared to non-prone healthy controls. Visual scanpath studies show that healthy individuals tend to direct more foveal fixations to the feature areas (eyes, nose, mouth) of threat-related facial expressions (anger, fear). By contrast, delusion-prone individuals exhibit reduced foveal attention to threat-related faces, combined with �extended� scanpaths, that may be interpreted as an attentional pattern of �vigilance-avoidance� for social threat. Chapters 5 and 6 extend the work presented in Chapters 3 and 4, by investigating the presence of similar behavioural and attentional biases in deluded schizophrenia, compared to healthy control and non-deluded schizophrenia groups. Deluded schizophrenia subjects exhibited a similar delay in processing angry faces, compared to non-prone control participants, while both deluded and non-deluded schizophrenia groups displayed a generalised affect recognition deficit. Visual scanpath investigations revealed a similar style of avoiding a broader range of negative (anger, fear, sad) faces in deluded schizophrenia, as well as a common pattern of fewer fixations with shorter duration, and reduced attention to facial features of all faces in both deluded and non-deluded schizophrenia. The examination of inferential biases for emotions displayed in facial expressions is presented in Chapter 7 in a study of causal attributional style. The results of this study provide some support for a �self-serving� bias in deluded schizophrenia, as well as evidence for an inability to appreciate situational cues when making causal judgements in both delusion-prone and deluded schizophrenia. A theoretical integration of the current findings is presented in Chapter 8, with regard to the implications for cognitive theories of delusions, and neurobiological models of schizophrenia phenomena, more generally. Visual attention biases for threat-related facial expressions in delusion-prone and deluded schizophrenia are consistent with proposals of neural dysconnectivity between frontal-limbic networks, while attributional biases and impaired facial expression perception may reflect dysfunction in a broader �social brain� network encompassing these and medial temporal lobe regions. Strong evidence for attentional biases and affect recognition deficits in delusion-prone individuals implicates their role in the development of delusional beliefs, but the weaker evidence for attributional biases in delusion-prone individuals suggests that inferential biases about others� emotions may be relevant only to the maintenance of delusional beliefs (or that attributional biases for others� emotional states may reflect other, trait-linked difficulties related to mentalising ability). In summary, the work presented in this thesis demonstrates the utility of adopting a single-symptom approach to schizophrenia within the continuum framework, and attests to the importance of further investigations of aberrant social cognition in relation to the development of delusions.
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Meyer, Eric C. "A visual scanpath study of facial affect recognition in schizotypy and social anxiety." Diss., Online access via UMI:, 2005.

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Castner, Nora Jane [Verfasser]. "Gaze and visual scanpath features for data-driven expertise recognition in medical image inspection / Nora Jane Castner." Tübingen : Universitätsbibliothek Tübingen, 2020. http://d-nb.info/1223451429/34.

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Harding, Glen, and Marina Bloj. "Real and predicted influence of image manipulations on eye movements during scene recognition." 2010. http://hdl.handle.net/10454/4716.

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In this paper, we investigate how controlled changes to image properties and orientation affect eye movements for repeated viewings of images of natural scenes. We make changes to images by manipulating low-level image content (such as luminance or chromaticity) and/or inverting the image. We measure the effects of these manipulations on human scanpaths (the spatial and chronological path of fixations), additionally comparing these effects to those predicted by a widely used saliency model (L. Itti & C. Koch, 2000). Firstly we find that repeated viewing of a natural image does not significantly modify the previously known repeatability (S. A. Brandt & L. W. Stark, 1997; D. Noton & L. Stark, 1971) of scanpaths. Secondly we find that manipulating image features does not necessarily change the repeatability of scanpaths, but the removal of luminance information has a measurable effect. We also find that image inversion appears to affect scene perception and recognition and may alter fixation selection (although we only find an effect on scanpaths with the additional removal of luminance information). Additionally we confirm that visual saliency as defined by L. Itti and C. Koch's (2000) model is a poor predictor of real observer scanpaths and does not predict the small effects of our image manipulations on scanpaths.
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Book chapters on the topic "Visual scanpaths"

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Duan, Lijuan, Haitao Qiao, Chunpeng Wu, Zhen Yang, and Wei Ma. "Modeling of Human Saccadic Scanpaths Based on Visual Saliency." In Advances in Intelligent Systems and Computing, 267–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01796-9_28.

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Eraslan, Sukru, Yeliz Yesilada, and Simon Harper. "Identifying Patterns in Eyetracking Scanpaths in Terms of Visual Elements of Web Pages." In Lecture Notes in Computer Science, 163–80. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08245-5_10.

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Cerf, Moran, Jonathan Harel, Alex Huth, Wolfgang Einhäuser, and Christof Koch. "Decoding What People See from Where They Look: Predicting Visual Stimuli from Scanpaths." In Attention in Cognitive Systems, 15–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00582-4_2.

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Teng, Clare, Harshita Sharma, Lior Drukker, Aris T. Papageorghiou, and J. Alison Noble. "Towards Scale and Position Invariant Task Classification Using Normalised Visual Scanpaths in Clinical Fetal Ultrasound." In Simplifying Medical Ultrasound, 129–38. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87583-1_13.

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Assens, Marc, Xavier Giro-i-Nieto, Kevin McGuinness, and Noel E. O’Connor. "PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks." In Lecture Notes in Computer Science, 406–22. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-11021-5_25.

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Zangemeister, Wolfgang H., and Ulrich Oechsner. "Evidence for scanpaths in hemianopic patients shown through string editing methods." In Visual Attention and Cognition, 197–221. Elsevier, 1996. http://dx.doi.org/10.1016/s0166-4115(96)80078-1.

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Stark, Lawrence W., and Yun S. Choi. "Experimental metaphysics: The scanpath as an epistemological mechanism." In Visual Attention and Cognition, 3–69. Elsevier, 1996. http://dx.doi.org/10.1016/s0166-4115(96)80069-0.

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Conference papers on the topic "Visual scanpaths"

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Chen, Zhenzhong, and Wanjie Sun. "Scanpath Prediction for Visual Attention using IOR-ROI LSTM." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/89.

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Predicting scanpath when a certain stimulus is presented plays an important role in modeling visual attention and search. This paper presents a model that integrates convolutional neural network and long short-term memory (LSTM) to generate realistic scanpaths. The core part of the proposed model is a dual LSTM unit, i.e., an inhibition of return LSTM (IOR-LSTM) and a region of interest LSTM (ROI-LSTM), capturing IOR dynamics and gaze shift behavior simultaneously. IOR-LSTM simulates the visual working memory to adaptively integrate and forget scene information. ROI-LSTM is responsible for predicting the next ROI given the inhibited image features. Experimental results indicate that the proposed architecture can achieve superior performance in predicting scanpaths.
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Raptis, George E., and Christina Katsini. "Analyzing Scanpaths From A Field Dependence-Independence Perspective When Playing A Visual Search Game." In ETRA '21: 2021 Symposium on Eye Tracking Research and Applications. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448018.3459655.

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Drusch, Gautier, and J. M. Christian Bastien. "Analyzing visual scanpaths on the Web using the mean shift procedure and T-pattern detection." In the 2012 Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2652574.2653432.

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Carette, Romuald, Mahmoud Elbattah, Federica Cilia, Gilles Dequen, Jean-Luc Guérin, and Jérôme Bosche. "Learning to Predict Autism Spectrum Disorder based on the Visual Patterns of Eye-tracking Scanpaths." In 12th International Conference on Health Informatics. SCITEPRESS - Science and Technology Publications, 2019. http://dx.doi.org/10.5220/0007402601030112.

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Goldberg, Joseph H., and Jonathan I. Helfman. "Visual scanpath representation." In the 2010 Symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1743666.1743717.

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Verma, Ashish, and Debashis Sen. "HMM-based Convolutional LSTM for Visual Scanpath Prediction." In 2019 27th European Signal Processing Conference (EUSIPCO). IEEE, 2019. http://dx.doi.org/10.23919/eusipco.2019.8902643.

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Ho, Yeuk F., and Lawrence W. Stark. "Scanpath-based model for visual tracking of telerobots." In Electronic Imaging, edited by Bernice E. Rogowitz and Thrasyvoulos N. Pappas. SPIE, 2000. http://dx.doi.org/10.1117/12.387198.

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Han, Rui, and Shuangjiu Xiao. "Human Visual Scanpath Prediction Based on RGB-D Saliency." In the 2018 International Conference. New York, New York, USA: ACM Press, 2018. http://dx.doi.org/10.1145/3191442.3191463.

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Li, Aoqi, and Zhenzhong Chen. "Individual trait oriented scanpath prediction for visual attention analysis." In 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017. http://dx.doi.org/10.1109/icip.2017.8296982.

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Li, Aoqi, Yingxue Zhang, and Zhenzhong Chen. "Scanpath mining of eye movement trajectories for visual attention analysis." In 2017 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2017. http://dx.doi.org/10.1109/icme.2017.8019507.

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