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

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樓主: 搖尾乞憐
51#
發(fā)表于 2025-3-30 10:38:43 | 只看該作者
One-Shot-Learning Gesture Recognition Using HOG-HOF Features,together with variants of a Dynamic Time Warping technique. Both methods outperform other published methods and help narrow the gap between human performance and algorithms on this task. The code is publicly available in the MLOSS repository.
52#
發(fā)表于 2025-3-30 13:29:18 | 只看該作者
Transfer Learning Decision Forests for Gesture Recognition,e manifold structure of the feature space. We show that both of them are important to achieve higher accuracy. Our experiments demonstrate improvements over traditional decision forests in the ChaLearn Gesture Challenge and MNIST data set. They also compare favorably against other state-of-the-art classifiers.
53#
發(fā)表于 2025-3-30 18:36:35 | 只看該作者
Book 2017ages and multi-modal RGB-Depth image sequences. It offers a comprehensive review of vision-based approaches for supervised gesture recognition methods that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different source
54#
發(fā)表于 2025-3-30 23:50:50 | 只看該作者
2520-131X e reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures..978-3-319-86059-6978-3-319-57021-1Series ISSN 2520-131X Series E-ISSN 2520-1328
55#
發(fā)表于 2025-3-31 01:54:55 | 只看該作者
Richard F. Link,George S. Koch Jr.ferring the optimal labeling of this hierarchical model. The pose information captured by this hierarchical model can also be used as a intermediate representation for other high-level tasks. We demonstrate it in action recognition from static images.
56#
發(fā)表于 2025-3-31 07:36:10 | 只看該作者
57#
發(fā)表于 2025-3-31 12:04:34 | 只看該作者
Discriminative Hierarchical Part-Based Models for Human Parsing and Action Recognition,ferring the optimal labeling of this hierarchical model. The pose information captured by this hierarchical model can also be used as a intermediate representation for other high-level tasks. We demonstrate it in action recognition from static images.
58#
發(fā)表于 2025-3-31 13:33:46 | 只看該作者
59#
發(fā)表于 2025-3-31 20:43:54 | 只看該作者
60#
發(fā)表于 2025-3-31 22:14:46 | 只看該作者
Book 2017 that have been validated by various challenges. Several aspects of gesture recognition are reviewed, including data acquisition from different sources, feature extraction, learning, and recognition of gestures..
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