人工ニューラルネットワークによるリアルタイム連続ジェスチャスポッティング
Real-Time and Continuous Hand Gesture Spotting: an Approach Based on Artificial Neural Networks
データグローブを用い、2つのANNを直列に組み合わせて連続的なハンドジェスチャの区間検出と認識をリアルタイムで行う手法を提案し、高い認識率を実現した。
著者: Pedro Neto, Dário Pereira, Norberto Pires, Paulo Moreira
分類: cs.RO, cs.CV
原文アブストラクト
New and more natural human-robot interfaces are of crucial interest to the evolution of robotics. This paper addresses continuous and real-time hand gesture spotting, i.e., gesture segmentation plus gesture recognition. Gesture patterns are recognized by using artificial neural networks (ANNs) specifically adapted to the process of controlling an industrial robot. Since in continuous gesture recognition the communicative gestures appear intermittently with the noncommunicative, we are proposing a new architecture with two ANNs in series to recognize both kinds of gesture. A data glove is used as interface technology. Experimental results demonstrated that the proposed solution presents high recognition rates (over 99% for a library of ten gestures and over 96% for a library of thirty gestures), low training and learning time and a good capacity to generalize from particular situations.
