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Action Recognition From Depth Maps Using Deep Convolutional Neural Networks
This paper proposes a new method, i.e., weighted hierarchical depth motion maps (WHDMM) + three-channel deep convolutional neural networks (3ConvNets), for human action recognition from depth maps onExpand
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Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
Recently, Convolutional Neural Networks (ConvNets) have shown promising performances in many computer vision tasks, especially image-based recognition. How to effectively use ConvNets for video-basedExpand
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Joint Distance Maps Based Action Recognition With Convolutional Neural Networks
Motivated by the promising performance achieved by deep learning, an effective yet simple method is proposed to encode the spatio-temporal information of skeleton sequences into color texture images,Expand
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Skeleton Optical Spectra-Based Action Recognition Using Convolutional Neural Networks
This letter presents an effective method to encode the spatiotemporal information of a skeleton sequence into color texture images, referred to as skeleton optical spectra, and employs convolutionalExpand
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ConvNets-Based Action Recognition from Depth Maps through Virtual Cameras and Pseudocoloring
In this paper, we propose to adopt ConvNets to recognize human actions from depth maps on relatively small datasets based on Depth Motion Maps (DMMs). In particular, three strategies are developed toExpand
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Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks
Abstract Convolutional Neural Networks (ConvNets) have recently shown promising performance in many computer vision tasks, especially image-based recognition. How to effectively apply ConvNets toExpand
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Salient Object Detection via Weighted Low Rank Matrix Recovery
Image-based salient object detection is a useful and important technique, which can promote the efficiency of several applications such as object detection, image classification/retrieval, objectExpand
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A Spectral and Spatial Approach of Coarse-to-Fine Blurred Image Region Detection
Blur exists in many digital images, it can be mainly categorized into two classes: defocus blur which is caused by optical imaging systems and motion blur which is caused by the relative motionExpand
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RGB-D-based action recognition datasets: A survey
Human action recognition from RGB-D (Red, Green, Blue and Depth) data has attracted increasing attention since the first work reported in 2010. Over this period, many benchmark datasets have beenExpand
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RGB-D-based Human Motion Recognition with Deep Learning: A Survey
Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much attention. Along withExpand
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