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8下载：
步态识别算法代码，对多种识别算法予以实现，以及一些论文上提到方法的测试程序。-Gait recognition algorithm code for a variety of recognition algorithms to be realized, as well as some papers on the method of testing procedures mentioned.
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Gait extraction toolbox which is used in matlab abd very useful for human activity recognition
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人体运动视觉分析主要包括运动目标检测、 运动 目标分类 、 人体运动跟踪、 人体行为识别与描述四个环
节 ， 在多领域具有广阔的应用前景． 本文从上述四个方面综述了人体运动分析的研究现状， 对人体运动分析的热点
难点进行讨论 ， 对可能的发展方向进行阐述和展望．-Visual analysis includes moving object detection,moving object classfication,human tracking and activity recogni
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本书从机器学习的角度介绍了基于视觉的运动分析领域的最新算法和系统。-Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visua
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Centinela is a human activity recognition system based on data from an accelerometer and sensor unit. This is powerpoint presentation on a pervasive compurting application.-Centinela is a human activity recognition system based on data from an accele
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Human Activity Recognition in Thermal Infrared Imagery
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A feature selection based framework for human activity recognition using wearable multimodal sensors
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In this programe, a four-dimensional spatiotemporal shape context
descr iptor is introduced and used for human activity recognition in video
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skeleton based human activity recognition
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This a knn test file, used for human activity recognition, the knn is based on matlab knn algorithm.-This is a knn test file, used for human activity recognition, the knn is based on matlab knn algorithm.
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一份用tensorflow平台做的cnn分类时序信号，是分类UCI 项目中的人体活动识别（HAR）数据集。该数据集包含原始的时序数据和经预处理的数据（包含 561 个特征）(A CNN classification timing signal made by tensorflow platform is a human activity recognition (HAR) dataset in the classified UCI project. The dataset contains or
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与经典的方法相比，使用具有长时间记忆细胞的递归神经网络(RNN)不需要或几乎不需要特征工程。数据可以直接输入到神经网络中，神经网络就像一个黑匣子，可以正确地对问题进行建模。其他研究在活动识别数据集上可以使用大量的特征工程，这是一种与经典数据科学技术相结合的信号处理方法。这里的方法在数据预处理的数量方面非常简单(Compared with the classical methods, the recursive neural network (RNN) with long-term memory
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