21,518 research outputs found

    Glimpse: A gaze-based measure of temporal salience

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    Temporal salience considers how visual attention varies over time. Although visual salience has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored, despite arguably being of utmost importance to understand the temporal evolution of attention on dynamic contents. To address this gap, we proposed GLIMPSE, a novel measure to compute temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure is conceptually simple, training free, and provides a semantically meaningful quantification of visual attention over time. As an extension, we explored scoring algorithms to estimate temporal salience from spatial salience maps predicted with existing computational models. However, these approaches generally fall short when compared with our proposed gaze-based measure. GLIMPSE could serve as the basis for several downstream tasks such as segmentation or summarization of videos. GLIMPSE’s software and data are publicly available

    Investigating the timecourse of accessing conversational implicatures during incremental sentence interpretation

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    Many contextual inferences in utterance interpretation are explained as following from the nature of conversation and the assumption that participants are rational. Recent psycholinguistic research has focussed on certain of these ‘Gricean’ inferences and have revealed that comprehenders can access them in online interpretation. However there have been mixed results as to the time-course of access. Some results show that Gricean inferences can be accessed very rapidly, as rapidly as any other contextually specified information (Sedivy, 2003; Grodner, Klein, Carbery, & Tanenhaus, 2010); while other studies looking at the same kind of inference suggest that access to Gricean inferences are delayed relative to other aspects of semantic interpretation (Huang & Snedeker, 2009; in press). While previous timecourse research has focussed on Gricean inferences that support the online assignment of reference to definite expressions, the study reported here examines the timecourse of access to scalar implicatures, which enrich the meaning of an utterance beyond the semantic interpretation. Even if access to Gricean inference in support of reference assignment may be rapid, it is still unknown whether genuinely enriching scalar implicatures are delayed. Our results indicate that scalar implicatures are accessed as rapidly as other contextual inferences. The implications of our results are discussed in reference to the architecture of language comprehension

    Egocentric video summarisation via purpose-orientedframe scoring and selection

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    Existing video summarisation techniques are quite generic in nature, since they generally overlook the important aspect of what actual purpose the summary will be serving. In sharp contrast with this mainstream work, it can be acknowledged that there are many possible purposes the same videos can be summarised for. Accordingly, we consider a novel perspective: summaries with a purpose. This work is an attempt to both, call the attention on this neglected aspect of video summarisation research, and to illustrate it and explore it with two concrete purposes, focusing on first-person-view videos. The proposed purpose-oriented summarisation techniques are framed under the common (frame-level) scoring and selection paradigm, and have been tested on two egocentric datasets, BEOID and EGTEA-Gaze+. The necessary purpose-specific evaluation metrics are also introduced. The proposed approach is compared with two purpose-agnostic summarisation baselines. On the one hand, a partially agnostic method uses the scores obtained by the proposed approach, but follows a standard generic frame selection technique. On the other hand, the fully agnostic method do not use any purpose-based information, and relies on generic concepts such as diversity and representativeness. The results of the experimental work show that the proposed approaches compare favourably with respect to both baselines. More specifically, the purpose-specific approach generally produces summaries with the best compromise between summary lengths and favourable purpose-specific metrics. Interestingly, it is also observed that results of the partially-agnostic baseline tend to be better than those of the fully-agnostic one. These observations provide strong evidence on the advantage and relevance of purpose-specific summarisation techniques and evaluation metrics, and encourage further work on this important subject.Funding for open access charge: CRUE-Universitat Jaume
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