54,522 research outputs found

    The DRIVE-SAFE project: signal processing and advanced information technologies for improving driving prudence and accidents

    Get PDF
    In this paper, we will talk about the Drivesafe project whose aim is creating conditions for prudent driving on highways and roadways with the purposes of reducing accidents caused by driver behavior. To achieve these primary goals, critical data is being collected from multimodal sensors (such as cameras, microphones, and other sensors) to build a unique databank on driver behavior. We are developing system and technologies for analyzing the data and automatically determining potentially dangerous situations (such as driver fatigue, distraction, etc.). Based on the findings from these studies, we will propose systems for warning the drivers and taking other precautionary measures to avoid accidents once a dangerous situation is detected. In order to address these issues a national consortium has been formed including Automotive Research Center (OTAM), Koç University, Istanbul Technical University, Sabancı University, Ford A.S., Renault A.S., and Fiat A. Ş

    Multimodal person recognition for human-vehicle interaction

    Get PDF
    Next-generation vehicles will undoubtedly feature biometric person recognition as part of an effort to improve the driving experience. Today's technology prevents such systems from operating satisfactorily under adverse conditions. A proposed framework for achieving person recognition successfully combines different biometric modalities, borne out in two case studies

    A multi-modal dance corpus for research into real-time interaction between humans in online virtual environments

    Get PDF
    We present a new, freely available, multimodal corpus for research into, amongst other areas, real-time realistic interaction between humans in online virtual environments. The specific corpus scenario focuses on an online dance class application scenario where students, with avatars driven by whatever 3D capture technology are locally available to them, can learn choerographies with teacher guidance in an online virtual ballet studio. As the data corpus is focused on this scenario, it consists of student/teacher dance choreographies concurrently captured at two different sites using a variety of media modalities, including synchronised audio rigs, multiple cameras, wearable inertial measurement devices and depth sensors. In the corpus, each of the several dancers perform a number of fixed choreographies, which are both graded according to a number of specific evaluation criteria. In addition, ground-truth dance choreography annotations are provided. Furthermore, for unsynchronised sensor modalities, the corpus also includes distinctive events for data stream synchronisation. Although the data corpus is tailored specifically for an online dance class application scenario, the data is free to download and used for any research and development purposes

    A critical investigation of the Osterwalder business model canvas: an in-depth case study

    Get PDF
    Although the Osterwalder business model canvas (BMC) is used by professionals worldwide, it has not yet been subject to a thorough investigation in academic literature. In this first contribution we present the results of an intensive, interactive process of data analysis, visual synthesis and textual rephrasing to gain insight into the business model of a single case (health television). The (textual and visual) representation of the business model needs to be consistent and powerful. Therefore, we start from the total value per customer segment. Besides the offer (or core value) additional value is created through customer related activities. The understanding of activities both on the strategic and tactical level reveals more insight into the total value creation. Moreover, value elements for one customer segment can induce value for others. The interaction between value for customer segments and activities results in a powerful customer value centred business model representation. Total value to customers generates activities and costs on the one hand and a revenue model on the other hand. Gross margins and sales volumes explain how value for customers contributes to profit. Another main challenge in business model mapping is in denominating the critical resources behind the activities. The Osterwalder business model canvas lacks consistency and power due to many overlaps which in turn are caused by the fixed architecture, the latter too easily leading to a filling-in exercise. Through its business model representation a company should first of all gain thorough understanding of it. Only then companies can evaluate the model and finally consider some adaptations
    corecore