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A Dataset for Persistent Multi-target Multi-camera Tracking in RGB-D

Ryan Layne, Sion Hannuna, Massimo Camplani, Jake Hall, Timothy M. Hospedales, Tao Xiang, Majid Mirmehdi, Dima Damen
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
In addition to raw data, we provide identity annotation for benchmarking, and tracking results from a contemporary RGB-D tracker -thus allowing focus on the higher level monitoring problems.  ...  To reflect the challenges of a realistic practical application, the dataset includes clothes changes and visitors to ensure the global reasoning is a realistic open-set problem.  ...  in an unconstrained manner.  ... 
doi:10.1109/cvprw.2017.189 dblp:conf/cvpr/LayneHCHHXMD17 fatcat:4eqjoeslffbmzmcbqe66rw4dqm

Guest editorial: web multimedia semantic inference using multi-cues

Yahong Han, Yi Yang, Xiaofang Zhou
2015 World wide web (Bussum)  
The paper "From constrained to unconstrained datasets an evaluation of local action descriptors and fusion strategies for interaction recognition" introduce a new unconstrained video dataset for interaction  ...  The results show the potential of the dataset to promote practical methods on interaction video recognition.  ... 
doi:10.1007/s11280-015-0360-2 fatcat:vc4plge5qvg7hfmza3dffmawki

High-level event recognition in unconstrained videos

Yu-Gang Jiang, Subhabrata Bhattacharya, Shih-Fu Chang, Mubarak Shah
2012 International Journal of Multimedia Information Retrieval  
However, due to the fast growing popularity of such videos, especially on the Web, solutions to this problem are in high demands and have attracted great interest from researchers.  ...  In this paper, we review current technologies for complex event recognition in unconstrained videos.  ...  Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.  ... 
doi:10.1007/s13735-012-0024-2 fatcat:mfzttic3svb4tho2xb6aczgp4y

A Fine Grainedresearch Over Human Action Recognition

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Human Action Recognition from videos has been an active research is in the computer vision due to its significant applicability in various real-time applications like video retrieval, human-robot interactions  ...  Unlike the earlier ones, this paper provides a detailed survey according to the basic working methodology of Human action recognition system.  ...  of subjects, they are categorized into two classes such as constrained and unconstrained.  ... 
doi:10.35940/ijitee.a4677.119119 fatcat:tacsukuctjehde4vzub5gzvfqu

Histogram of Oriented Gradient-Based Fusion of Features for Human Action Recognition in Action Video Sequences

Chirag I. Patel, Dileep Labana, Sharnil Pandya, Kirit Modi, Hemant Ghayvat, Muhammad Awais
2020 Sensors  
Human Action Recognition (HAR) is the classification of an action performed by a human. The goal of this study was to recognize human actions in action video sequences.  ...  The proposed approach is performed and compared with the state-of-the-art methods for action recognition on two publicly available benchmark datasets (KTH and Weizmann) and for cross-validation on the  ...  Acknowledgments: The authors would like to thank the reviewers for their valuable suggestions which helped in improving the quality of this paper.  ... 
doi:10.3390/s20247299 pmid:33353248 pmcid:PMC7766717 fatcat:n6b5qzdqd5cehcrwfkko3ywjnq

Effective Codebooks for Human Action Representation and Classification in Unconstrained Videos

Lamberto Ballan, Marco Bertini, Alberto Del Bimbo, Lorenzo Seidenari, Giuseppe Serra
2012 IEEE transactions on multimedia  
Recognition and classification of human actions for annotation of unconstrained video sequences has proven to be challenging because of the variations in the environment, appearance of actors, modalities  ...  It improves on previous contributions through the definition of a novel local descriptor that uses image gradient and optic flow to respectively model the appearance and motion of human actions at interest  ...  Each action, is represented by an histogram H of codewords w obtained according to k-means Fig. 3 :Fig. 5 : 35 Two fusion strategies: early-fusion (at the descriptor level) and late-fusion (at the codebook  ... 
doi:10.1109/tmm.2012.2191268 fatcat:f7r3w7clofgn3akdoxkmiszs4m

Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition

Stefan Mathe, Cristian Sminchisescu
2015 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Systems based on bag-of-words models from image features collected at maxima of sparse interest point operators have been used successfully for both computer visual object and action recognition tasks.  ...  of visual action and scene context recognition tasks.  ...  vision descriptors and fusion methods, leads to state of the art results in the Hollywood-2 and UCF-Sports action datasets.  ... 
doi:10.1109/tpami.2014.2366154 pmid:26352449 fatcat:i7estk2krzcvbhem3hfhq5vqjq

Being the center of attention: A Person-Context CNN framework for Personality Recognition [article]

Dario Dotti, Mirela Popa, Stylianos Asteriadis
2019 arXiv   pre-print
From a given scenario, we extract spatio-temporal motion descriptors from every individual in the scene, spatio-temporal motion descriptors encoding social group dynamics, and proxemics descriptors to  ...  Experiments on two public datasets demonstrate the effectiveness of jointly modeling the mutual Person-Context information, outperforming the state-of-the art-results for personality recognition in two  ...  ACKNOWLEDGMENTS This work has been funded by the European Union' Horizon 2020 Research and Innovation Programme under Grant Agreement N • 690090 (ICT4Life project).  ... 
arXiv:1910.06690v1 fatcat:ic6y3awyofeblmi5bfo2fre564

Recognizing Human Actions by Using Effective Codebooks and Tracking [chapter]

Lamberto Ballan, Lorenzo Seidenari, Giuseppe Serra, Marco Bertini, Alberto Del Bimbo
2013 Advanced Topics in Computer Vision  
Recognition and classification of human actions for annotation of unconstrained video sequences has proven to be challenging because of the variations in the environment, appearance of actors, modalities  ...  This variability reflects in the difficulty of defining effective descriptors and deriving appropriate and effective codebooks for action categorization.  ...  Local descriptors have shown better performance and are in principle better suited for videos taken in both constrained and unconstrained contexts.  ... 
doi:10.1007/978-1-4471-5520-1_3 dblp:series/acvpr/BallanSS13 fatcat:jcneb56tarbhtb7zelmarkddqe

A Review on Computer Vision-Based Methods for Human Action Recognition

Mahmoud Al-Faris, John Chiverton, David Ndzi, Ahmed Isam Ahmed
2020 Journal of Imaging  
Next, the most common datasets of human action recognition are presented.  ...  Human action recognition targets recognising different actions from a sequence of observations and different environmental conditions.  ...  In addition, DBNs based methods were used by [164] to learn features from an unconstrained video stream for human action recognition.  ... 
doi:10.3390/jimaging6060046 pmid:34460592 pmcid:PMC8321068 fatcat:eyp2pu6egzcunagferl7dhffay

Unconstrained Biometric Recognition: Summary of Recent SOCIA Lab. Research [article]

Varsha Balakrishnan
2020 arXiv   pre-print
The development of biometric recognition solutions able to work in visual surveillance conditions, i.e., in unconstrained data acquisition conditions and under covert protocols has been motivating growing  ...  This report summarises the research works published by elements of the SOCIA Lab. in the last decade in the scope of biometric recognition in unconstrained conditions.  ...  for extracting face descriptors from the LFW, IJB-A and MegaFace datasets.  ... 
arXiv:2001.09703v2 fatcat:hugkig4wxvgaldscwbobn6yhuy

The Automatic Detection of Chronic Pain-Related Expression: Requirements, Challenges and the Multimodal EmoPain Dataset

Min S. H. Aung, Sebastian Kaltwang, Bernardino Romera-Paredes, Brais Martinez, Aneesha Singh, Matteo Cella, Michel Valstar, Hongying Meng, Andrew Kemp, Moshen Shafizadeh, Aaron C. Elkins, Natalie Kanakam (+6 others)
2016 IEEE Transactions on Affective Computing  
First, through literature reviews, an overview of how pain is expressed in chronic pain and the motivation for detecting it in physical rehabilitation is provided.  ...  Natural unconstrained pain related facial expressions and body movement behaviours were elicited from people with chronic pain carrying out physical exercises.  ...  on a pre-segemented constrained dataset.  ... 
doi:10.1109/taffc.2015.2462830 pmid:30906508 pmcid:PMC6430129 fatcat:uvpdc6jzo5gibf5yu57uxos7wm

A Review on Human Activity Recognition Using Vision-Based Method

Shugang Zhang, Zhiqiang Wei, Jie Nie, Lei Huang, Shuang Wang, Zhen Li
2017 Journal of Healthcare Engineering  
Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions.  ...  For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations.  ...  Science and Technology Development Plan (no. 16-5-1-13-jch); and The Aoshan Innovation Project in Science and Technology of Qingdao National Laboratory for Marine Science and Technology (no. 2016ASKJ07  ... 
doi:10.1155/2017/3090343 pmid:29065585 pmcid:PMC5541824 fatcat:g6qbbbjpcref3p54kvquu5rltq

Joint Sparsity-Based Representation and Analysis of Unconstrained Activities

Raghuraman Gopalan
2013 2013 IEEE Conference on Computer Vision and Pattern Recognition  
We demonstrate the efficacy of our approach for activity classification and clustering by reporting competitive results on standard datasets such as, HMDB, UCF-50, Olympic Sports and KTH.  ...  We then present modeling strategies based on subspace-driven manifold metrics to characterize patterns among these components, across other videos in the system, to perform subsequent video analysis.  ...  While there has been a gamut of feature representations ranging from spatio-temporal volumes [13, 3] and trajectories [32, 42] to local interest point descriptors [36, 20] and action attributes  ... 
doi:10.1109/cvpr.2013.353 dblp:conf/cvpr/Gopalan13a fatcat:hdzjdfml7jfapaauu3vhlluyde

Face Recognition Using Smoothed High-Dimensional Representation [chapter]

Juha Ylioinas, Juho Kannala, Abdenour Hadid, Matti Pietikäinen
2015 Lecture Notes in Computer Science  
In this work, we propose application specific learning to train a separate BSIF descriptor for each of the local face regions.  ...  In detail, we provide a thorough evaluation on FERET and LFW benchmarks comparing our face representation method to the state-of-the-art in face recognition showing enhanced performance on FERET and promising  ...  FERET [14] is a standard dataset for benchmarking face recognition methods in constrained imaging conditions.  ... 
doi:10.1007/978-3-319-19665-7_44 fatcat:3to3xz35gbflho3secgo4bdelu
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