Titlebook: Gesture Recognition; Sergio Escalera,Isabelle Guyon,Vassilis Athitsos Book 2017 Springer International Publishing AG 2017 Artificial intel

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A. Menafoglio,A. Guadagnini,P. Secchition in sign language (SL) videos. Aff-SAM offers a compact and descriptive representation of hand configurations as well as regularized model-fitting, assisting hand tracking and extracting handshape features. We construct SA images representing the hand’s shape and appearance . landmark points. We

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Richard F. Link,George S. Koch Jr. models only considers rigid parts (e.g., torso, head, half limbs) guided by human anatomy. We argue that this representation of parts is not necessarily appropriate. In this paper, we introduce hierarchical poselets—a new representation for modeling the pose configuration of human bodies. Hierarchi

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https://doi.org/10.1007/978-3-642-58567-8t accuracy and multi-class support. In this paper, we present a novel method for transfer learning which uses decision forests, and we apply it to recognize gestures and characters. We introduce two mechanisms into the decision forest framework in order to transfer knowledge from the source tasks to

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Geostatistik in der Baugrundmodellierungh a demanding Kinect-based multimodal dataset, introduced in a recent gesture recognition challenge (CHALEARN 2013), where multiple subjects freely perform multimodal gestures. We employ multiple modalities, that is, visual cues, such as skeleton data, color and depth images, as well as audio, and w

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GEO SAR System Analysis and Design,ccessible for non-specialists. Emphasis is placed on ease of use, with a consistent, minimalist design that promotes accessibility while supporting flexibility and customization for advanced users. The toolkit features a broad range of classification and regression algorithms and has extensive suppo