Gesture interactions with video: From algorithms to user evaluation
Gesture interactions with video: From algorithms to user evaluation
复制标题
DOI：
10.1002/bltj.21577
复制
发表时间：
2013-03
影响因子：
--
通讯作者：
E. Marilly;A. Gonguet;O. Martinot;Frédérique Pain
中科院分区：
文献类型：
--
作者：
E. Marilly;A. Gonguet;O. Martinot;Frédérique Pain
在沉浸式通信旨在实现人、物体和环境之间的自然体验和交互的背景下，我们提出了一种通过用户和视频会议系统之间的手势识别来实现自然视频交互的方法。我们进行了一项端到端研究：我们从开发特定手势识别算法开始，最后通过用户评估来验证我们的结果。手势及其相关功能是通过用户调查确定的，该调查重点关注区分两个经常混淆的概念：手势和手势（即静态与动态）。我们的识别过程由两个主要任务组成：手势识别（即皮肤分割、背景扣除、区域组合、特征提取和分类）和手势识别（跟踪和识别）。我们的方法将信号相似性研究与动态手势识别的数据挖掘工具相结合。我们专注于实验和用户评估来改进我们的方法，考虑用户反馈并分析不同环境和不同用户的性能。
In the context of immersive communications that aim to enable natural experiences and interactions among people, objects, and the environment, we propose a method to enable natural video interactions through hand gesture recognition between users and a video meeting system. An end-to-end study was performed: we started with the development of specific gesture recognition algorithms and concluded with a user evaluation to validate our results. Gestures and their associated functionalities were identified via a user survey which focused on distinguishing two concepts which are often confused: hand posture and hand gesture (i.e., static versus dynamic). Our recognition process was composed of two main tasks: hand posture recognition (i.e., skin segmentation, background subtraction, region combination, feature extraction, and classification) and hand gesture recognition (tracking and recognition). Our approach combined a signal similarity study with a data-mining tool for dynamic gesture recognition. We focused on the experimentation and user evaluation to improve our approach, taking into account user feedback and analyzing performance in different environments and for different users.