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  • Association for Computing Machinery (ACM)  (2)
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  • Association for Computing Machinery (ACM)  (2)
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  • 1
    Online Resource
    Online Resource
    Association for Computing Machinery (ACM) ; 2022
    In:  ACM Transactions on Interactive Intelligent Systems Vol. 12, No. 3 ( 2022-09-30), p. 1-26
    In: ACM Transactions on Interactive Intelligent Systems, Association for Computing Machinery (ACM), Vol. 12, No. 3 ( 2022-09-30), p. 1-26
    Abstract: Sketching is an intuitive and simple way to depict sciences with various object form and appearance characteristics. In the past few years, widely available touchscreen devices have increasingly made sketch-based human-AI co-creation applications popular. One key issue of sketch-oriented interaction is to prepare input sketches efficiently by non-professionals because it is usually difficult and time-consuming to draw an ideal sketch with appropriate outlines and rich details, especially for novice users with no sketching skills. Thus, sketching brings great obstacles for sketch applications in daily life. On the other hand, hand-drawn sketches are scarce and hard to collect. Given the fact that there are several large-scale sketch datasets providing sketch data resources, but they usually have a limited number of objects and categories in sketch, and do not support users to collect new sketch materials according to their personal preferences. In addition, few sketch-related applications support the reuse of existing sketch elements. Thus, knowing how to extract sketches from existing drawings and effectively re-use them in interactive scene sketch composition will provide an elegant way for sketch-based image retrieval (SBIR) applications, which are widely used in various touch screen devices. In this study, we first conduct a study on current SBIR to better understand the main requirements and challenges in sketch-oriented applications. Then we develop the SketchMaker as an interactive sketch extraction and composition system to help users generate scene sketches via reusing object sketches in existing scene sketches with minimal manual intervention. Moreover, we demonstrate how SBIR improves from composited scene sketches to verify the performance of our interactive sketch processing system. We also include a sketch-based video localization task as an alternative application of our sketch composition scheme. Our pilot study shows that our system is effective and efficient, and provides a way to promote practical applications of sketches.
    Type of Medium: Online Resource
    ISSN: 2160-6455 , 2160-6463
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2022
    detail.hit.zdb_id: 2644997-3
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  • 2
    Online Resource
    Online Resource
    Association for Computing Machinery (ACM) ; 2021
    In:  Proceedings of the ACM on Human-Computer Interaction Vol. 5, No. CSCW1 ( 2021-04-13), p. 1-31
    In: Proceedings of the ACM on Human-Computer Interaction, Association for Computing Machinery (ACM), Vol. 5, No. CSCW1 ( 2021-04-13), p. 1-31
    Abstract: Chatbots systems, despite their popularity in today's HCI and CSCW research, fall short for one of the two reasons: 1) many of the systems use a rule-based dialog flow, thus they can only respond to a limited number of pre-defined inputs with pre-scripted responses; or 2) they are designed with a focus on single-user scenarios, thus it is unclear how these systems may affect other users or the community. In this paper, we develop a generalizable chatbot architecture (CASS) to provide social support for community members in an online health community. The CASS architecture is based on advanced neural network algorithms, thus it can handle new inputs from users and generate a variety of responses to them. CASS is also generalizable as it can be easily migrate to other online communities. With a follow-up field experiment, CASS is proven useful in supporting individual members who seek emotional support. Our work also contributes to fill the research gap on how a chatbot may influence the whole community's engagement.
    Type of Medium: Online Resource
    ISSN: 2573-0142
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2021
    detail.hit.zdb_id: 2930194-4
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