arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1607.06356cs.CV
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手语识别中的肢体关系推理

Reasoning about Body-Parts Relations for Sign Language Recognition

Universidad Politécnica de Valencia (UPV)(瓦伦西亚理工大学);KU Leuven(鲁汶大学)

Marc Martínez-Camarena, Jose Oramas, Mario Montagud-Climent, Tinne Tuytelaars

摘要:

多年来,手势识别主要是考虑孤立的手轨迹。然而,在大多数手语中,手势是在特定的上下文(身体区域)上定义的。我们提出了一个管道来执行手语识别,该管道使用MS Kinect传感器在3D空间中捕获的身体其他部位的上下文中对手部运动进行建模。此外,我们还根据手势过程中出现的不同手势进行手势识别。我们的实验表明,考虑不同的身体部位带来了更好的性能相比,其他方法只考虑全球的手轨迹。最后,我们证明了手势特征与手势特征的结合有助于提高对给定标志的预测。

英文摘要:

Over the years, hand gesture recognition has been mostly addressed considering hand trajectories in isolation. However, in most sign languages, hand gestures are defined on a particular context (body region). We propose a pipeline to perform sign language recognition which models hand movements in the context of other parts of the body captured in the 3D space using the MS Kinect sensor. In addition, we perform sign recognition based on the different hand postures that occur during a sign. Our experiments show that considering different body parts brings improved performance when compared to other methods which only consider global hand trajectories. Finally, we demonstrate that the combination of hand postures features with hand gestures features helps to improve the prediction of a given sign.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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