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Supporting activity recognition by visual analytics

机译：通过视觉分析支持活动识别

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Recognizing activities has become increasingly relevant in many application domains, such as security or ambient assisted living. To handle different scenarios, the underlying automated algorithms are configured using multiple input parameters. However, the influence and interplay of these parameters is often not clear, making exhaustive evaluations necessary. On this account, we propose a visual analytics approach to supporting users in understanding the complex relationships among parameters, recognized activities, and associated accuracies. First, representative parameter settings are determined. Then, the respective output is computed and statistically analyzed to assess parameters' influence in general. Finally, visualizing the parameter settings along with the activities provides overview and allows to investigate the computed results in detail. Coordinated interaction helps to explore dependencies, compare different settings, and examine individual activities. By integrating automated, visual, and interactive means users can select parameter values that meet desired quality criteria. We demonstrate the application of our solution in a use case with realistic complexity, involving a study of human protagonists in daily living with respect to hundreds of parameter settings.
机译：识别活动在许多应用领域中越来越重要，例如安全或环境辅助生活。要处理不同的方案，使用多个输入参数配置底层自动化算法。然而，这些参数的影响和相互作用通常不明确，使必要的详尽评估。在此帐户中，我们提出了一种可视化分析方法来支持用户了解参数，公认的活动和相关准确性的复杂关系。首先，确定代表参数设置。然后，计算各个输出和统计分析以评估参数的影响。最后，可视化参数设置以及活动提供概述，并允许详细研究计算的结果。协调的交互有助于探索依赖项，比较不同的设置，并检查各个活动。通过自动化，视觉和交互式集成，意味着用户可以选择满足所需质量标准的参数值。我们展示了我们在具有现实复杂性的用例中的解决方案的应用，涉及对人类主角的研究在日常生活中的几个参数设置。

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