High-level cinematic knowledge to predict inter-observer visual congruency - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2023

High-level cinematic knowledge to predict inter-observer visual congruency

Abstract

When watching the same visual stimulus, humans can exhibit a wide range of gaze behaviors. These variations can be caused by bottom-up factors (i.e. features of the stimulus itself) or top-down factors (i.e. characteristics of the observers). Inter-observer visual congruency is a measure of this range. Moreover, it has been shown that cinematic techniques, such as camera motion or shot editing, have a significant impact on this measure [17]. In this work, we first propose a metric for measuring IOC in videos, taking into account the dynamic nature of the stimuli. Then, we propose a model for predicting inter-observer visual congruency in the context of feature films, by using high-level cinematic annotation as prior information in a deep learning framework.
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hal-04139622 , version 1 (23-06-2023)

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Alexandre Bruckert, Marc Christie. High-level cinematic knowledge to predict inter-observer visual congruency. WICED x Cinemotions 2023 - Workshop on Intelligent Cinematography and Editing, and Emotions in Movies, Jun 2023, Nantes, France. pp.1-6, ⟨10.1145/3604321.3604331⟩. ⟨hal-04139622⟩
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