The expansion of touch-sensitive technologies, ranging from smartwatches to wall screens, triggered a wider use of gesture-based user interfaces and encouraged researchers to invent recognizers that are fast and accurate for end-users while being simple enough for practitioners. Since the pioneering work on two-dimensional (2D) stroke gesture recognition based on feature extraction and classification, numerous approaches and techniques have been introduced to classify uni- and multi-stroke gestures, satisfying various properties of articulation-, rotation-, scale-, and translation-invariance. As the domain abounds in different recognizers, it becomes difficult for the practitioner to choose the right recognizer, depending on the application and for the researcher to understand the state-of-the-art. To address these needs, a targeted literature review identified 16 significant 2D stroke gesture recognizers that were submitted to a descriptive analysis discussing their algorithm, performance, and properties, and a comparative analysis discussing their similarities and differences. Finally, some opportunities for expanding 2D stroke gesture recognition are drawn from these analyses.

中文翻译：

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二维笔画手势识别

触敏技术的扩展，从智能手表到壁屏，引发了基于手势的用户界面的更广泛使用，并鼓励研究人员发明对最终用户来说快速准确的识别器，同时对从业者来说足够简单。自从基于特征提取和分类的二维（2D）笔画手势识别的开创性工作以来，已经引入了许多方法和技术来对单笔和多笔手势进行分类，满足关节、旋转、缩放的各种特性。 , 和平移不变性。由于领域中存在大量不同的识别器，因此从业者很难根据应用选择正确的识别器，研究人员也很难了解最新技术。为了解决这些需求，有针对性的文献回顾确定了 16 个重要的 2D 笔画手势识别器，这些识别器被提交给讨论其算法、性能和属性的描述性分析，以及讨论它们的异同的比较分析。最后，从这些分析中得出了一些扩展 2D 笔画手势识别的机会。