Empirical Comics Research

Kirtley, Clare; Murray, Christopher; Vaughan, Phillip; Tatler, Benjamin W.

doi:10.4324/9781315185354

Cited by 22 publications

(5 citation statements)

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“…Although this SPECT theory is silent with regard to codality switching and integration, it is reasonable to assume that the integration costs observed in the present set of experiments can be traced back to encodingthat is frontend processing. Studying these integration costs using eyetracking methods seems to be an auspicious approach as eye-tracking studies have shown that comic readers spend more time on panels also including texts as compared to panels with just pictorial content (Chiba, Tanaka, Shoji, & Toyama, 2007;Laubrock, Hohenstein, & Kümmerer, 2018). Such a study could also address the alternative explanation of the present findings according to which codality switching just surprises participants.…”

Section: Theoretical Implicationsmentioning

confidence: 79%

Cross-codal integration of bridging-event information in narrative understanding

et al. 2020

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Visual narratives communicate event sequences by using different code systems such as pictures and texts. Thus, comprehenders must integrate information from different codalities. This study addressed such cross-codal integration processes by investigating how the codality of bridging-event information (i.e., pictures, text) affects the understanding of visual narrative events. In Experiment 1, bridging-event information was either present (as picture or text) or absent (i.e., not shown). The viewing times for the subsequent picture depicting the end state of the action were comparable within the absent and the text conditions. Further, the viewing times for the end-state picture were significantly longer in the text condition as compared to the pictorial condition. In Experiment 2, we tested whether replacing bridging-event information with a blank panel increases viewing times in a way similar to the text condition. Bridging event information was either present (as picture) or absent (not shown vs. blank panel). The results replicated Experiment 1. Additionally, the viewing times for the end-state pictures were longest in the blank condition. In Experiment 3, we investigated the costs related to integrating information from different codalities by directly comparing the text and picture conditions with the blank condition. The results showed that the distortion caused by the blank panel is larger than the distortion caused by cross-codal integration processes. Summarizing, we conclude that cross-codal information processing during narrative comprehension is possible but associated with additional mental effort. We discuss the results with regard to theories of narrative understanding.

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Section: Theoretical Implicationsmentioning

confidence: 79%

Cross-codal integration of bridging-event information in narrative understanding

et al. 2020

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show abstract

“…Although this SPECT theory is silent with regard to codality switching and integration, it is reasonable to assume that the integration costs observed in the present set of experiments can be traced back to encoding, that is frontend processing. Studying these integration costs using eyetracking methods seems to be an auspicious approach as eye-tracking studies have shown that comic readers spend more time on panels also including texts as compared to panels with just pictorial content (Chiba, Tanaka, Shoji, & Toyama, 2007;Laubrock, Hohenstein, & Kümmerer, 2018). Such a study could also address the alternative explanation of the present findings according to which codality switching just surprises participants.…”

Section: Theoretical Implicationsmentioning

confidence: 79%

Cross-Codal Integration of Bridging Event Information in Narrative Understanding

Huff¹,

Rosenfelder²,

Oberbeck³

et al. 2019

Preprint

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Visual narratives communicate event sequences by using different code systems such as pictures and texts. Thus, comprehenders must integrate information from different codalities. This study addressed such cross-codal integration processes by investigating how the codality of bridging event information (i.e. pictures, text) affects the understanding of visual narrative events. In Experiment 1, bridging event information was either present (as picture or text) or absent (i.e. not shown). The viewing times for the subsequent picture depicting the end state of the action were comparable within the absent and the text conditions. Further, the viewing times for the end state picture were significantly longer in the text condition as compared to the pictorial condition. In Experiment 2, we tested whether replacing bridging event information with a blank panel increases viewing times in a way similar to the text condition. Bridging event information was either present (as picture) or absent (not shown vs. blank panel). The results replicated Experiment 1. Additionally, the viewing times for the end state pictures were longest in the blank condition. In Experiment 3, we investigated the costs related to integrating information from different codalities by directly comparing the text and picture conditions with the blank condition. The results showed that the distortion caused by the blank panel is larger than the distortion caused by cross-codal integration processes. Summarizing, we conclude that cross-codal information processing during narrative comprehension is possible but associated with additional mental effort. We discuss the results with regard to theories of narrative understanding.

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“…Laubrock and Dubray [23] have similarly shown that deep convolutional neural networks are well-suited to capture graphical aspects of comics books and can successfully be used in categorizing illustrator style, pacing the way for a visual stylometry. Laubrock et al [24] show that eye-tracking data obtained from comics readers as a measure of visual attention and CNN predictions of empirical saliency based on Deep Gaze II [22] tend to focus on similar regions of comics pages. Regions containing text such as speech balloons or captions are focused most often.…”

Section: A Related Workmentioning

confidence: 99%

“…The individual elements just mentioned can also be distributed across several panels or bleed into the void between panels called the "gutter". Recent overviews of comics research can be found in Cohn [7], Augereau et al [3], and Dunst et al [12]. Here we focus on one particular element of graphic structure, namely, speech balloons.…”

Section: Introductionmentioning

confidence: 99%

Deep CNN-Based Speech Balloon Detection and Segmentation for Comic Books

Dubray

Laubrock

2019

2019 International Conference on Document Analysis and Recognition (ICDAR)

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We develop a method for the automated detection and segmentation of speech balloons in comic books, including their carrier and tails. Our method is based on a deep convolutional neural network that was trained on annotated pages of the Graphic Narrative Corpus. More precisely, we are using a fully convolutional network approach inspired by the U-Net architecture, combined with a VGG-16 based encoder. The trained model delivers state-of-the-art performance with an F1-score of over 0.94. Qualitative results suggest that wiggly tails, curved corners, and even illusory contours do not pose a major problem. Furthermore, the model has learned to distinguish speech balloons from captions. We compare our model to earlier results and discuss some possible applications.

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Empirical Comics Research

Cited by 22 publications

References 0 publications

Cross-codal integration of bridging-event information in narrative understanding

Cross-codal integration of bridging-event information in narrative understanding

Cross-Codal Integration of Bridging Event Information in Narrative Understanding

Deep CNN-Based Speech Balloon Detection and Segmentation for Comic Books

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