An affective model of user experience for interactive art

Gilroy, Stephen W.; Cavazza, Marc; Chaignon, Rémi; Mäkelä, Satu-Marja; Niranen, Markus; André, Elisabeth; Vogt, Thurid; Urbain, Jérôme; Seichter, Hartmut; Billinghurst, Mark; Benayoun, Maurice

doi:10.1145/1501750.1501774

Cited by 20 publications

(15 citation statements)

References 17 publications

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“…Optical flow descriptors were previously used in the literature (e.g. [11]) to model the arousal levels of users. Arousal is a feature that is prominent in several models of affect [22,24].…”

Section: Measuring Visual Affectmentioning

confidence: 99%

Design and implementation of an affect-responsive interactive photo frame

Dibeklioğlu

Kosunen

Zuzanek

et al. 2011

J Multimodal User Interfaces

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This paper describes an affect-responsive interactive photo-frame application that offers its user a different experience with every use. It relies on visual analysis of activity levels and facial expressions of its users to select responses from a database of short video segments. This ever-growing database is automatically prepared by an offline analysis of user-uploaded videos. The resulting system matches its user's affect along dimensions of valence and arousal, and gradually adapts its response to each specific user. In an extended mode, two such systems are coupled and feed each other with visual content. The strengths and weaknesses of the system are assessed through a usability study, where a Wizard-of-Oz response logic is contrasted with the fully automatic system that uses affective and activity-based features, either alone, or in tandem.

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Section: Measuring Visual Affectmentioning

confidence: 99%

Design and implementation of an affect-responsive interactive photo frame

Dibeklioğlu

Kosunen

Zuzanek

et al. 2011

J Multimodal User Interfaces

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“…In fact, several wrapper classes to efficient vision toolboxes are already part of the current implementation of SSI. This concerns OpenCV 4 , a library for real-time image processing, ARToolKitPlus 5 , a library for real-time marker tracking, and SHORE 6 , a library for face and object detection and fine analysis. From our lab we have integrated EmoVoice and AuBT 7 .…”

Section: Incorporated Toolsmentioning

confidence: 99%

“…For this purpose, a novel fusion mechanism explored in [4] was integrated. It is based on the PAD model and measures emotional response along three dimensions: pleasure (P), arousal (A) and dominance (D).…”

Section: Fusionmentioning

confidence: 99%

Smart sensor integration: A framework for multimodal emotion recognition in real-time

Wagner

André

Jung

2009

2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops

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Affect sensing by machines has been argued as an essential part of next-generation human-computer interaction (HCI). To this end, in the recent years a large number of studies have been conducted, which report automatic recognition of emotion as a difficult, but feasible task. However, most effort has been put towards offline analysis, whereas to date only few applications exist, which are able to react to a user's emotion in real-time. In response to this deficit we introduce a framework we call Smart Sensor Integration (SSI), which considerably jump-starts the development of multimodal online emotion recognition (OER) systems. In particular SSI supports the pattern recognition pipeline by offering tailored tools for data segmentation, feature extraction, and pattern recognition, as well as, tools to apply them offline (training phase) and online (real-time recognition). Furthermore, it has been designed to handle input from various input modalities and to suit the fusion of multimodal information.

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“…As we have previously described [17], the affective multimodal fusion system generates a PAD vector representation for a number of affective modalities, including speech, physical interactions and movement and interest detection. Each PAD vector is The PAD values of the overall vector are sent to an L-system generation component that maps each dimension of the PAD emotional model to parameters controlling the growth and appearance of the tree.…”

Section: Multimodal Detection Of Affective Statesmentioning

confidence: 99%

“…(Emotional Tree) [16,17]. Based on an Augmented Reality system, this artwork provides a 3-D visual representation of an organically growing tree, reacting to user emotions and physical manipulations.…”

Section: Introductionmentioning

confidence: 99%