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Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection [article]

Mahdyar Ravanbakhsh, Moin Nabi, Hossein Mousavi, Enver Sangineto, Nicu Sebe
2018 arXiv   pre-print
Most of the crowd abnormal event detection methods rely on complex hand-crafted features to represent the crowd motion and appearance.  ...  We specifically propose a novel measure-based method which allows measuring the local abnormality in a video by combining semantic information (inherited from existing CNN models) with low-level Optical-Flow  ...  We then introduced a simple yet effective unsupervised measure to capture temporal CNN patterns in video frames.  ... 
arXiv:1610.00307v3 fatcat:rovycoirzzfvbplvekra3rmvti

2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29

2019 IEEE transactions on circuits and systems for video technology (Print)  
., TCSVT Feb. 2019 375-389 Discriminative Spatio-Temporal Pattern Discovery for 3D Action Recognition.  ...  ., +, TCSVT July 2019 1919-1932 Combined Static and Motion Features for Deep-Networks-Based Activity Recognition in Videos.  ... 
doi:10.1109/tcsvt.2019.2959179 fatcat:2bdmsygnonfjnmnvmb72c63tja

Bodyprint-A Meta-Feature Based LSTM Hashing Model for Person Re-Identification

Danilo Avola, Luigi Cinque, Alessio Fagioli, Gian Luca Foresti, Daniele Pannone, Claudio Piciarelli
2020 Sensors  
In this paper, for the first time in the state-of-the-art, a meta-feature based Long Short-Term Memory (LSTM) hashing model for person re-identification is presented.  ...  arise to important visual appearance changes of people, for example, clothes, lighting, and occlusions; thus making person re-identification a very hard task.  ...  A last competitor is reported in Reference [50] , where a deep attention based Siamese model to jointly learn spatio-temporal expressive video representations and similarity metrics is presented.  ... 
doi:10.3390/s20185365 pmid:32962168 pmcid:PMC7570836 fatcat:oudnmfpxpbccvfver3vwtfb5jy

2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30

2020 IEEE transactions on circuits and systems for video technology (Print)  
., TCSVT Jan. 2020 217-231 Hu, X., see Zhu, L., TCSVT Oct. 2020 3358-3371 Hu, Y., Lu, M., Xie, C., and Lu, X  ...  ., and Zeng, B., MUcast: Linear Uncoded Multiuser TCSVT Nov. 2020 4299-4308 Hu, R., see Chen, L., TCSVT Dec. 2020 4513-4525 Hu, R., see Wang, X., TCSVT Nov. 2020 4309-4320 Hu, X., see Zhang, X  ...  ., +, TCSVT Dec. 2020 4663-4675 Hidden Markov models Jointly Learning Visual Poses and Pose Lexicon for Semantic Action Recog- nition.  ... 
doi:10.1109/tcsvt.2020.3043861 fatcat:s6z4wzp45vfflphgfcxh6x7npu

Deep Learning Techniques for Future Intelligent Cross-Media Retrieval [article]

Sadaqat ur Rehman, Muhammad Waqas, Shanshan Tu, Anis Koubaa, Obaid ur Rehman, Jawad Ahmad, Muhammad Hanif, Zhu Han
2020 arXiv   pre-print
These challenges are evaluated on deep learning (DL) based methods, which are categorized into four main groups: 1) unsupervised methods, 2) supervised methods, 3) pairwise based methods, and 4) rank based  ...  The fundamental objective of this work is to exploit Deep Neural Networks (DNNs) for bridging the "media gap", and provide researchers and developers with a better understanding of the underlying problems  ...  [117] proposed Deep Visual-Semantic Hashing (DVSH) model, which utilized two different DNN models such as CNN and Long Short Term Memory (LSTM) to learn similar representation for visual data and natural  ... 
arXiv:2008.01191v1 fatcat:t63bg55w2vdqjcprzaaidrmprq

Mid-level Representation for Visual Recognition [article]

Moin Nabi
2015 arXiv   pre-print
The mid-level patterns can be extracted from images and videos using the motion and appearance information of visual phenomenas.  ...  The mid-level image/video representation involves discovering and training a set of mid-level visual patterns (e.g., parts and attributes) and represent a given image/video utilizing them.  ...  The mid-level patterns can be extracted from images and videos using the motion and appearance information of visual phenomenas.  ... 
arXiv:1512.07314v1 fatcat:knmhkwxqk5aczis7ce6g2sv2wm

Unsupervised human activity analysis for intelligent mobile robots

Paul Duckworth, David C. Hogg, Anthony G. Cohn
2019 Artificial Intelligence  
dimensional representation of common and repeated patterns from multiple encoded visual observations.  ...  without the need for manual temporal segmentation, which can be time consuming and costly.  ...  Qualitative spatial and temporal calculi arise from a set of jointly exhaustive and pairwise disjoint (JEPD) relations.  ... 
doi:10.1016/j.artint.2018.12.005 fatcat:vq56rrsuojfq3kzr3ip3tj4d74

Generative Models for Novelty Detection: Applications in abnormal event and situational change detection from data series [article]

Mahdyar Ravanbakhsh
2019 arXiv   pre-print
In this thesis, we propose several methods to model the novelty detection problem in unsupervised and semi-supervised fashion.  ...  Novelty detection is a process for distinguishing the observations that differ in some respect from the observations that the model is trained on.  ...  Their dedication to my education provided the foundation for my studies.  ... 
arXiv:1904.04741v1 fatcat:fdwhsuaoi5hcdbjzcbjh2z6ydu

A comprehensive study of visual event computing

WeiQi Yan, Declan F. Kieran, Setareh Rafatirad, Ramesh Jain
2010 Multimedia tools and applications  
We start by presenting events and their classifications, and continue with discussing the problem of capturing events in terms of photographs, videos, etc, as well as the methodologies for event storing  ...  We introduce each component of a visual event computing system, and its computational aspects, we discuss the progress of each component and review its overall status.  ...  This work was partially supported by QUB research project: Unusual event detection in audio-visual surveillance for public transport (NO.D6223EEC).  ... 
doi:10.1007/s11042-010-0560-9 fatcat:ak6u3eefefgjhmbpr7asru3n7u

On Learning Semantic Representations for Million-Scale Free-Hand Sketches [article]

Peng Xu, Yongye Huang, Tongtong Yuan, Tao Xiang, Timothy M. Hospedales, Yi-Zhe Song, Liang Wang
2020 arXiv   pre-print
We propose a dual-branch CNNRNN network architecture to represent sketches, which simultaneously encodes both the static and temporal patterns of sketch strokes.  ...  Specifically, we use our dual-branch architecture as a universal representation framework to design two sketch-specific deep models: (i) We propose a deep hashing model for sketch retrieval, where a novel  ...  visual concepts and RNN to model human sketching temporal orders, respectively.  ... 
arXiv:2007.04101v1 fatcat:cng2cw6r5fg43p5erfisj57tu4

A self-organizing neural network architecture for learning human-object interactions [article]

Luiza Mici, German I. Parisi, Stefan Wermter
2018 arXiv   pre-print
Our model consists of a hierarchy of Grow-When-Required (GWR) networks that learn prototypical representations of body motion patterns and objects, accounting for the development of action-object mappings  ...  In this paper, we present a self-organizing neural network for the recognition of human-object interactions from RGB-D videos.  ...  Acknowledgments The authors gratefully acknowledge partial support by the EU-and City of Hamburg-funded program Pro-Exzellenzia 4.0, the German Research Foundation DFG under project CML (TRR 169), and  ... 
arXiv:1710.01916v2 fatcat:eu7c7wn3anfx5hjzabufbrrdvq

Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends [article]

Asmat Zahra, Nazia Perwaiz, Muhammad Shahzad, Muhammad Moazam Fraz
2022 arXiv   pre-print
In this context, a comprehensive review of current re-ID approaches in solving theses challenges is needed to analyze and focus on particular aspects for further advancements.  ...  Person re-identification (Re-ID) is one of the primary components of an automated visual surveillance system.  ...  in viewpoint, place, background, resolution and different visual appearance.  ... 
arXiv:2202.13121v1 fatcat:luwwbcwspndqpauj4dosmmojee

2021 Index IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 43

2022 IEEE Transactions on Pattern Analysis and Machine Intelligence  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  ., +, TPAMI March 2021 1110-1118 Learning Energy-Based Spatial-Temporal Generative ConvNets for Dynamic Patterns.  ... 
doi:10.1109/tpami.2021.3126216 fatcat:h6bdbf2tdngefjgj76cudpoyia

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
-that appeared in this periodical during 2021, and items from previous years that were commented upon or corrected in 2021.  ...  Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name.  ...  Yang, K., +, TIP 2021 1866-1881 Jointly Modeling Motion and Appearance Cues for Robust RGB-T Tracking.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

Deep Learning for Free-Hand Sketch: A Survey [article]

Peng Xu, Timothy M. Hospedales, Qiyue Yin, Yi-Zhe Song, Tao Xiang, Liang Wang
2022 arXiv   pre-print
(iii) Promotion of future work via a discussion of bottlenecks, open problems, and potential research directions for the community.  ...  (ii) A review of the developments of free-hand sketch research in the deep learning era, by surveying existing datasets, research topics, and the state-of-the-art methods through a detailed taxonomy and  ...  This upgraded model can be jointly trained from both supervised and unsupervised data, and obtained significant performance improvements.  ... 
arXiv:2001.02600v3 fatcat:lek5sivzsrat3i52lqh2eifnia
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