Event Segmentation

Zacks, Jeffrey M.; Swallow, Khena M.

doi:10.1111/j.1467-8721.2007.00480.x

Cited by 354 publications

(284 citation statements)

References 15 publications

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“…Although Wayang generates explanations after each input, there is some evidence that people sometimes construct explanations only when their predictions fail (Leake, 1995;Zacks & Swallow, 2007). We plan to do a deeper literature review on this question, and perhaps to alter Wayang accordingly.…”

Section: Resultsmentioning

confidence: 99%

Using modified incremental chart parsing to ascribe intentions to animated geometric figures

et al. 2011

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People spontaneously ascribe intentions on the basis of observed behavior, and research shows that they do this even with simple geometric figures moving in a plane. The latter fact suggests that 2-D animations isolate critical information-object movement-that people use to infer the possible intentions (if any) underlying observed behavior. This article describes an approach to using motion information to model the ascription of intentions to simple figures. Incremental chart parsing is a technique developed in natural-language processing that builds up an understanding as text comes in one word at a time. We modified this technique to develop a system that uses spatiotemporal constraints about simple figures and their observed movements in order to propose candidate intentions or nonagentive causes. Candidates are identified via partial parses using a library of rules, and confidence scores are assigned so that candidates can be ranked. As observations come in, the system revises its candidates and updates the confidence scores. We describe a pilot study demonstrating that people generally perceive a simple animation in a manner consistent with the model.

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Section: Resultsmentioning

confidence: 99%

Using modified incremental chart parsing to ascribe intentions to animated geometric figures

et al. 2011

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“…For example, the visualization strategy is based on findings on the role of (1) segmentation of complex events [15], and (2) a first-person perspective [16] for human perception and action learning. However, it must be added that a third-person perspective (e.g., a student watching the teacher performing) has its own benefits with respect to action learning [16].…”

Section: Discussionmentioning

confidence: 99%

“…Concerning the visualization of basic step models, we take into account two aspects involving the perception and understanding of complex multimodal events, like dance figures. First, research has shown that segmentation of ongoing activity into smaller units is an automatic component of human perception and functional for memory and learning processes [1,15]. For this, we applied algorithms that segment the continuous stream of motion information into a concatenation of elementary gestures (i.e., dance steps) matching the beat pattern in the music (cf., [6]).…”

Section: User-and Body-centered Approachmentioning

confidence: 99%

Dance-the-Music: an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates

Maes

Amelynck

Leman

2012

EURASIP J. Adv. Signal Process.

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In this article, a computational platform is presented, entitled "Dance-the-Music", that can be used in a dance educational context to explore and learn the basics of dance steps. By introducing a method based on spatiotemporal motion templates, the platform facilitates to train basic step models from sequentially repeated dance figures performed by a dance teacher. Movements are captured with an optical motion capture system. The teachers' models can be visualized from a first-person perspective to instruct students how to perform the specific dance steps in the correct manner. Moreover, recognition algorithms-based on a template matching method-can determine the quality of a student's performance in real time by means of multimodal monitoring techniques. The results of an evaluation study suggest that the Dance-the-Music is effective in helping dance students to master the basics of dance figures.

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“…Studies have consistently shown that people's experiences of the world consist of segmenting the ongoing flow of perceptual information into discrete events instead of passively responding to stimuli (Zacks & Swallow, 2007). Event boundaries are of utmost importance in event perception, because they are the breakpoints where significant changes in both perceptual and conceptual representations take place.…”

Section: Introductionmentioning

confidence: 99%

An Empirical and Computational Investigation of Perceiving and Remembering Event Temporal Relations

Harter

Graesser

2009

Cognitive Science

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Events have beginnings, ends, and often overlap in time. A major question is how perceivers come to parse a stream of multimodal information into meaningful units and how different event boundaries may vary event processing. This work investigates the roles of these three types of event boundaries in constructing event temporal relations. Predictions were made based on how people would err according to the beginning state, end state, and overlap heuristic hypotheses. Participants viewed animated events that include all the logical possibilities of event temporal relations, and then made temporal relation judgments. The results showed that people make use of the overlap between events and take into account the ends and beginnings, but they weight ends more than beginnings. Neural network simulations showed a self-organized distinction when learning temporal relations between events with overlap versus those without.

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Event Segmentation

Cited by 354 publications

References 15 publications

Using modified incremental chart parsing to ascribe intentions to animated geometric figures

Using modified incremental chart parsing to ascribe intentions to animated geometric figures

Dance-the-Music: an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates

An Empirical and Computational Investigation of Perceiving and Remembering Event Temporal Relations

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