Results 31 to 40 of about 461,436 (263)

Action Recognition From Thermal Videos

IEEE Access, 2019
Human action recognition using a camera-based surveillance system remains a challenging task. In particular, action recognition is difficult when a human is not visible in an image captured in a dark environment.
Ganbayar Batchuluun, Dat Tien Nguyen, Tuyen Danh Pham, Chanhum Park, Kang Ryoung Park   +4 more
doaj   +1 more source

3D trajectories for action recognition [PDF]

2014 IEEE International Conference on Image Processing (ICIP), 2014
Recent development in affordable depth sensors opens new possibilities in action recognition problem. Depth information improves skeleton detection, therefore many authors focused on analyzing pose for action recognition. But still skeleton detection is not robust and fail in more challenging scenarios, where sensor is placed outside of optimal working
Koperski, Michal, Bilinski, Piotr, Bremond, François   +2 more
openaire   +2 more sources

Model recommendation for action recognition [PDF]

2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012
Simply choosing one model out of a large set of possibilities for a given vision task is a surprisingly difficult problem, especially if there is limited evaluation data with which to distinguish among models, such as when choosing the best “walk” action classifier from a large pool of classifiers tuned for different viewing angles, lighting conditions,
Pyry Matikainen, Rahul Sukthankar, Martial Hebert   +2 more
openaire   +1 more source

Human Action Recognition Method Based on Action-Time Perception [PDF]

Jisuanji gongcheng
To address the problem of redundant information in action videos and the sparse distribution of feature channels in action information, a 3D residual network based on action-time perception is proposed.
WANG Xiaolu, WEN Jianrong
doaj   +1 more source

Statistical Machine Learning for Human Behaviour Analysis

Entropy, 2020
Human behaviour analysis has introduced several challenges in various fields, such as applied information theory, affective computing, robotics, biometrics and pattern recognition [...]
Thomas B. Moeslund, Sergio Escalera, Gholamreza Anbarjafari, Kamal Nasrollahi, Jun Wan   +4 more
doaj   +1 more source

Cross-Channel Graph Convolutional Networks for Skeleton-Based Action Recognition

IEEE Access, 2021
In recent years, skeleton-based action recognition, graph convolutional networks, have achieved remarkable performance. In these existing works, the features of all nodes in the neighbor set are aggregated into the updated features of the root node ...
Jun Xie, Wentian Xin, Ruyi Liu, Lijie Sheng, Xiangzeng Liu, Xuesong Gao, Sheng Zhong, Lei Tang, Qiguang Miao   +8 more
doaj   +1 more source

Data Mining for Action Recognition [PDF]

, 2015
In recent years, dense trajectories have shown to be an efficient representation for action recognition and have achieved state-of-the-art results on a variety of increasingly difficult datasets. However, while the features have greatly improved the recognition scores, the training process and machine learning used hasn’t in general deviated from the ...
Andrew Gilbert, Richard Bowden
openaire   +2 more sources

Feature seeding for action recognition [PDF]

2011 International Conference on Computer Vision, 2011
Progress in action recognition has been in large part due to advances in the features that drive learning-based methods. However, the relative sparsity of training data and the risk of overfitting have made it difficult to directly search for good features. In this paper we suggest using synthetic data to search for robust features that can more easily
Pyry Matikainen, Rahul Sukthankar, Martial Hebert   +2 more
openaire   +1 more source

Action recognition by discriminative EdgeBoxes

IET Computer Vision, 2018
Due to the huge number of online videos uploaded and viewed every day, there is an emerging need nowadays for the action recognition techniques. Applying these techniques in uncontrolled and realistic videos is still a challenging task, considering the ...
Mohammed El‐Masry, Mohamed Waleed Fakhr, Mohammed A.‐M. Salem   +2 more
doaj   +1 more source

Compressed video ensemble based pseudo-labeling for semi-supervised action recognition

Machine Learning with Applications, 2022
Some recent studies have focused on deep learning based semi-supervised learning for action recognition. However, it is difficult to scale up their training because their input is RGB frames, the obtainment of which incurs computational and storage costs.
Hayato Terao, Wataru Noguchi, Hiroyuki Iizuka, Masahito Yamamoto   +3 more
doaj   +1 more source