Convolutional two-stream network fusion for video action recognition[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 1933-1941. 原文下载地址:Convolutional Two-Stream Network Fusion for Video Action Recognition 这是来自格拉茨科技大学的一篇论文,于 2016 年被计算机...
Human action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and recognition is relatively old, yet not well-understood by the students and research communi...
ComputervisionHuman action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and搂recognition is relatively old, yet not well-understood by the students and ...
Lampert, Christoph H., Matthew B. Blaschko, and Thomas Hofmann. "Beyond sliding windows: Object localization by efficient subwindow search." Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008. Code online:https://sites.google.com/site/christophlampert/softwar...
“Two-Stream Convolutional Networks for Action Recognition in Videos”(2014NIPS) Two Stream方法最初在这篇文章中被提出,基本原理为对视频序列中每两帧计算密集光流,得到密集光流的序列(即temporal信息)。然后对于视频图像(spatial)和密集光流(temporal)分别训练CNN模型,两个分支的网络分别对动作的类别进行判断,最后...
有关action recognition in videos, 最近自己也在搞这方面的东西,该领域水很深,不过其实主流就那几招,我就班门弄斧说下video里主流的: Deep Learning之前最work的是INRIA组的Improved Dense Trajectories(IDT) + fisher vector, paper and code: LEAR - Improved Trajectories Video Description ...
Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the future state. Vision-based action recognition and prediction from videos are such tasks, where action recognition is to infer human actions (pr...
Human action recognition in visual data is one of the most fundamental challenges in computer vision. Existing approaches for this primary goal have been based on video data, often incorporating both color and dynamic flow information. Nevertheless, the majority of the visual data constitute still im...
The recognition of human actions in video streams is a challenging task in computer vision, with cardinal applications in brain–computer interfaces and surveillance, for example. Recently, deep learning has produced remarkable results, but it can be hard to use in practice, as its training require...
Action Recognition is an active research area in computer vision and among the action recognition tasks Violent action recognition has high importance as it can be used for safety and security enforcement. Design of Intelligent robots and Intelligent Surveillance systems that can automatically detect viol...