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Extraction and Classification of Diving Clips from Continuous Video Footage
[article]
2017
arXiv
pre-print
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The techniques proposed can be easily generalized to video footage recorded from other sports. ...
In order to automate this kind of task, three challenging sub-problems are often encountered: 1) temporally cropping events/actions of interest from continuous video; 2) tracking the object of interest ...
Firstly, we extract individual video clips of dives from continuous video footage. ...
arXiv:1705.09003v1
fatcat:gzk575zigrgwjiripwvnvbvxbi
Extraction and Classification of Diving Clips from Continuous Video Footage
2017
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
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The techniques proposed can be easily generalized to video footage recorded from other sports. ...
In order to automate this kind of task, three challenging sub-problems are often encountered: 1) temporally cropping events/actions of interest from continuous video; 2) tracking the object of interest ...
Firstly, we extract individual video clips of dives from continuous video footage. ...
doi:10.1109/cvprw.2017.18
dblp:conf/cvpr/NibaliHMG17
fatcat:2tjy23yqzrfbjeihr3ylqs6iha
A probabilistic template-based approach to discovering repetitive patterns in broadcast videos
2005
Proceedings of the 13th annual ACM international conference on Multimedia - MULTIMEDIA '05
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Finally, we verify each probabilistic template by measuring the similarities between the video subsegments and the template. Evaluations on various sports videos show promising results. ...
There are usually repetitive sub-segments in broadcast videos, which may be associated with high-level concepts or events, e.g., news footage, repeated scores in basketball. ...
This has an added benefit: the system is more tolerant of classification errors resulted from video decomposition and symbolization. ...
doi:10.1145/1101149.1101238
dblp:conf/mm/WangLY05
fatcat:lhri6pexzvh7jhjvbnbkcmth24
TechWare: Video-Based Human Action Detection Resources [Best of the Web
2010
IEEE Signal Processing Magazine
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In the early days, human bodies were tracked and segmented from the videos to characterize actions and motion trajectories are popularly used to represent and recognize actions. ...
The feature extraction is accelerated through the use of approximate box-filter operations on an integral video structure. ...
., and a Fellow of the IEEE. ...
doi:10.1109/msp.2010.937496
fatcat:56rypucynneohale67doue3avy
A research tool for long-term and continuous analysis of fish assemblage in coral-reefs using underwater camera footage
2014
Ecological Informatics
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Two characteristics set our system apart from traditional ecological data collecting and processing methods. First, the continuous video recording results in enormous data volumes of monitoring data. ...
We present a research tool that supports marine ecologists' research by allowing analysis of long-term and continuous fish monitoring video content. ...
With a larger user base and the assistance from the marine ecology community, we can extend and improve this tool to fit into specific needs of the users and generate more valuable results for the marine ...
doi:10.1016/j.ecoinf.2013.10.006
fatcat:my7dwck43ng7fgt6qed7kuonni
Improving a 3-D Convolutional Neural Network Model Reinvented from VGG16 with Batch Normalization
2019
2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
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In this paper, two models reinvented from VGG16 are created with and without using Batch Normalization to evaluate their model performance. ...
The technique introduced in this paper shows a fast, reliable and accurate estimation of human activity type and could be used in smart environments. ...
The Video Pre-Processing method is presented in Fig.3 Fig. 4 (Model 1) , consists of two sections, feature extraction and classification. ...
doi:10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00052
dblp:conf/uic/PattanajakM19
fatcat:7ctiikkmsfcjfd64ynguwnvtfu
Mining Automatically Estimated Poses from Video Recordings of Top Athletes
2018
International Journal of Computer Science in Sport
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Therefore, plenty of noisy pose data will soon be available from videos recorded at a regular and frequent basis. ...
This work is among the first to develop mining algorithms that can mine the expected abundance of noisy and annotation-free pose data from video recordings in individual sports. ...
He thanks the many colleagues from FXPAL (Lynn Wilcox, Mitesh Patel, Andreas Girgensohn, Yan-Ying Chen, Tony Dunnigan, Chidansh Bhatt, Qiong Liu, Matthew Lee and many more) who greatly assisted the research ...
doi:10.2478/ijcss-2018-0005
fatcat:6gsxqvubqvgshl4uepdbody6im
Mining Automatically Estimated Poses from Video Recordings of Top Athletes
[article]
2018
arXiv
pre-print
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Therefore, plenty of noisy pose data will soon be available from videos recorded at a regular and frequent basis. ...
This work is among the first to develop mining algorithms that can mine the expected abundance of noisy and annotation-free pose data from video recordings in individual sports. ...
He thanks the many colleagues from FXPAL (Lynn Wilcox, Mitesh Patel, Andreas Girgensohn, Yan-Ying Chen, Tony Dunnigan, Chidansh Bhatt, Qiong Liu, Matthew Lee and many more) who greatly assisted the research ...
arXiv:1804.08944v2
fatcat:oeawsqtqgrgwpitqn35js7ibhu
A Survey of Vision-Based Human Action Evaluation Methods
2019
Sensors
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The benchmark datasets from this research field and some evaluation criteria employed to validate the algorithms' performance are introduced. ...
This paper presents a comprehensive survey of approaches and techniques in action evaluation research, including motion detection and preprocessing using skeleton data, handcrafted feature representation ...
Acknowledgments: The authors would like to thank the anonymous reviewers for their valuable and insightful comments on an earlier version of this manuscript. ...
doi:10.3390/s19194129
pmid:31554229
pmcid:PMC6806217
fatcat:zgwsdv6xorfvxjck6rsjusezwe
ReHAR: Robust and Efficient Human Activity Recognition
[article]
2018
arXiv
pre-print
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Then, both video frames and their corresponding optical flow images are fed into a Single Frame Representation Model to generate representations. ...
First, we generate an optical flow image for each video frame. ...
UCF Sports Action Dataset: The UCF Sports dataset 5 [36] consists of a set of actions collected from a wide range of stock footage websites including BBC Motion gallery and GettyImages. ...
arXiv:1802.09745v1
fatcat:hsbk7b7arrhwlmwdzufubz2jl4
Cognitive Load Estimation in the Wild
2018
Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18
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On this 3-class problem, our best proposed method of using 3D convolutional neural networks achieves 86.1% accuracy at predicting task-induced cognitive load in a sample of 92 subjects from video alone ...
Given the size of the dataset, and the inherent complexity of cognitive load estimation as a task, especially in a real-world environment, the results are impressive for both HMM and ...
The views and conclusions being expressed are those of the authors, and have not been sponsored, approved, or endorsed by Toyota or plaintiffs class counsel. ...
doi:10.1145/3173574.3174226
dblp:conf/chi/FridmanRMF18
fatcat:v32oxr2qs5fkfjkc4halcesek4
Submersible- and lander-observed community patterns in the Mariana and New Britain trenches: Influence of productivity and depth on epibenthic and scavenging communities
2015
Deep Sea Research Part I: Oceanographic Research Papers
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sources, based on the presence of terrestrial debris in submersible video footage. ...
Five submersible dives conducted using the DEEPSEA CHALLENGER submersible generated video of undisturbed deep-sea communities at bathyal (994 m), abyssal (3755 m), and hadal (8228 m) depths in the New ...
and enhancement; Christina Symons for generously sharing cruise metadata and for producing Figure 1 ; Ron Allum and the many DEEPSEA CHALLENGE Expedition team members who made the recovery of the video ...
doi:10.1016/j.dsr.2014.12.012
fatcat:67p777ycfbc6bocan5kfxiqtia
Machine and deep learning for sport-specific movement recognition: a systematic review of model development and performance
2018
Journal of Sports Sciences
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Model development for movement recognition were predominantly undertaken using supervised classification approaches. ...
A kernel form of the Support Vector Machine algorithm was used in 53% of IMU and 50% of vision-based studies. ...
Extraction and classification of diving 867 clips from continuous video footage. ArXiv, pre-print. Retrieved from 868 https://arxiv.org/pdf/1705.09003.pdf 869 O'Reilly, M. A., Whelan, D. F., Ward, T. ...
doi:10.1080/02640414.2018.1521769
pmid:30307362
fatcat:h3flbavuivbilbo6ekwvmnjg6i
A Hough transform-based voting framework for action recognition
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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We present a method to classify and localize human actions in video using a Hough transform voting framework. ...
Using low-level features such as gradients and optical flow, we demonstrate that Hough-voting can achieve state-of-the-art performance on several datasets covering a wide range of action-recognition scenarios ...
This research has been supported by funding from the Swiss National Foundation NCCR project IM2. Angela Yao was also supported by funding from NSERC Canada. ...
doi:10.1109/cvpr.2010.5539883
dblp:conf/cvpr/YaoGG10
fatcat:7d6slbftqvhbzafwsykupd2laq
Automatic Round-the-Clock Detection of Whales for Mitigation from Underwater Noise Impacts
2013
PLoS ONE
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Our results demonstrate that thermal imaging can be used for reliable and continuous marine mammal protection. ...
It outperforms alerted observers in terms of number of detected blows and ship-whale encounters. ...
The support by crew and officers of RV Polarstern and Reederei Laisz during the expeditions and the installation of the thermal scanner is greatly appreciated. S. ...
doi:10.1371/journal.pone.0071217
pmid:23951113
pmcid:PMC3741354
fatcat:6jot37ux6batvhamsuv6zhgyei
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