Understanding and localizing activities from correspondences of clustered trajectories-Reference-Cited by-同舟云学术

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Understanding and localizing activities from correspondences of clustered trajectories

Published:2017-06 Issue: Volume:159 Page:128-142
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Turchini Francesco,Seidenari Lorenzo^ORCID,Del Bimbo Alberto

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference67 articles.

1. Good practice in large-scale learning for image classification;Akata;IEEE Trans. Pattern Anal. Mach. Intell.,2014

2. Automatic recognition of offensive team formation in american football plays;Atmosukarto,2013

3. Video event classification using string kernels;Ballan;Multimed. Tools Appl.,2010

4. Recognising team activities from noisy data;Bialkowski,2013

5. Efficient match kernel between sets of features for visual recognition;Bo,2009

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1. Joint-Based Action Progress Prediction;Sensors;2023-01-03

2. Group-of-features relevance in multinomial kernel logistic regression and application to human interaction recognition;Expert Systems with Applications;2020-06

3. Notice of Retraction: An Improved High-Density Sub Trajectory Clustering Algorithm;IEEE Access;2020

4. Unsupervised learning from videos using temporal coherency deep networks;Computer Vision and Image Understanding;2019-02

5. Global-Local Temporal Saliency Action Prediction;IEEE Transactions on Image Processing;2018-05

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