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Temporal Action Co-Segmentation in 3D Motion Capture Data and Videos

Konstantinos Papoutsakis, Costas Panagiotakis, Antonis A. Argyros
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Given two action sequences, we are interested in spotting/co-segmenting all pairs of sub-sequences that represent the same action. We propose a totally unsupervised solution to this problem.  ...  Due to the generic problem formulation and solution, the proposed method can be applied to motion capture (i.e., 3D skeletal) data or to conventional RGB videos acquired in the wild.  ...  The work in [52] introduces an unsupervised learning algorithm using absorbing Markov chain in order to detect a common activity of variable length from a set of videos or multiple instances of it in  ... 
doi:10.1109/cvpr.2017.231 dblp:conf/cvpr/PapoutsakisPA17 fatcat:zd6ycphggve4ja2ihkpyrbv3ja

Object Discovery From a Single Unlabeled Image by Mining Frequent Itemset With Multi-scale Features [article]

Runsheng Zhang, Yaping Huang, Mengyang Pu, Jian Zhang, Qingji Guan, Qi Zou, Haibin Ling
2020 arXiv   pre-print
We also evaluate our approach compared with unsupervised saliency detection methods and achieves competitive results on seven benchmark datasets.  ...  Specifically, we first convert the feature maps from a pre-trained CNN model into a set of transactions, and then discovers frequent patterns from transaction database through pattern mining techniques  ...  Later MC [41] separates salient objects from the background via absorbing Markov chain.  ... 
arXiv:1902.09968v3 fatcat:2col2budbjgzjoykscdl632qv4

Salient Object Detection: A Survey [article]

Ali Borji, Ming-Ming Cheng, Qibin Hou, Huaizu Jiang, Jia Li
2018 arXiv   pre-print
Detecting and segmenting salient objects in natural scenes, often referred to as salient object detection, has attracted a lot of interest in computer vision.  ...  Covering 228 publications, we survey i) roots, key concepts, and tasks, ii) core techniques and main modeling trends, and iii) datasets and evaluation metrics in salient object detection.  ...  The saliency of each superpixel is computed as the absorbed time for the transient node to the absorbing nodes of the Markov Chain.  ... 
arXiv:1411.5878v5 fatcat:aw7pqd554zdfblokxy2zgp35z4

Automatic visual detection of human behavior: A review from 2000 to 2014

Palwasha Afsar, Paulo Cortez, Henrique Santos
2015 Expert systems with applications  
., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic.  ...  Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection.  ...  a chain of primitives namely, straightforward activities and actions.  ... 
doi:10.1016/j.eswa.2015.05.023 fatcat:3f7nze4slnhavkhin45jfe5bwi

Salient object detection: A survey

Ali Borji, Ming-Ming Cheng, Qibin Hou, Huaizu Jiang, Jia Li
2019 Computational Visual Media  
Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision.  ...  Covering 228 publications, we survey i) roots, key concepts, and tasks, ii) core techniques and main modeling trends, and iii) datasets and evaluation metrics for salient object detection.  ...  [99] formulate saliency detection via absorbing Markov chains, in which the transient and absorbing nodes are superpixels around the image center and border respectively.  ... 
doi:10.1007/s41095-019-0149-9 fatcat:rwh3mzauinfj7na5ewo6wfp26e

Visual Affordance and Function Understanding: A Survey [article]

Mohammed Hassanin, Salman Khan, Murat Tahtali
2018 arXiv   pre-print
Furthermore, we cover functional scene understanding and the prevalent functional descriptors used in the literature.  ...  Specifically, we discuss sub-problems such as affordance detection, categorization, segmentation and high-level reasoning.  ...  [16] learned the human activities from RGB-D videos considering object affordances.  ... 
arXiv:1807.06775v1 fatcat:kl7miygnizdinpovqnzfdhwokq

Visual Object Tracking by Segmentation with Graph Convolutional Network [article]

Bo Jiang, Panpan Zhang, Lili Huang
2020 arXiv   pre-print
Segmentation-based tracking has been actively studied in computer vision and multimedia. Superpixel based object segmentation and tracking methods are usually developed for this task.  ...  [11] propose to use Absorbing Markov Chain (AMC) model for super-pixel segmentation.  ...  [11] present a tracking-by-segmentation framework using absorbing markov model to better distinguish the foreground and background. Lee et al.  ... 
arXiv:2009.02523v2 fatcat:n7va34d54nbrzbnj33ne55fqxq

Pedestrian Models for Autonomous Driving Part I: low level models, from sensing to tracking [article]

Fanta Camara, Nicola Bellotto, Serhan Cosar, Dimitris Nathanael, Matthias Althoff, Jingyuan Wu, Johannes Ruenz, André Dietrich, Charles W. Fox
2020 arXiv   pre-print
image detection to high-level psychology models, from the perspective of an AV designer.  ...  This self-contained Part I covers the lower levels of this stack, from sensing, through detection and recognition, up to tracking of pedestrians.  ...  of the Bayesian filter, derived from MCMC, which draws a set of samples and builds Markov chains over the target state space.  ... 
arXiv:2002.11669v1 fatcat:fgg5j5jdwrbujjgtj2uhgrx2am

Discovering Primary Objects in Videos by Saliency Fusion and Iterative Appearance Estimation

Jiong Yang, Gangqiang Zhao, Junsong Yuan, Xiaohui Shen, Zhe Lin, Brian Price, Jonathan Brandt
2016 IEEE transactions on circuits and systems for video technology (Print)  
We also propose a new video dataset containing 51 videos for primary object detection with per-frame ground truth labeling.  ...  In this paper, we propose a new method for detecting primary objects in unconstrained videos in a completely automatic setting.  ...  detects the saliency of each superpixel as its absorbing time in an Absorbed Markov Chain.  ... 
doi:10.1109/tcsvt.2015.2433171 fatcat:j36vuagvujauhoeplcttngwo64

Deep Learning in Mobile and Wireless Networking: A Survey [article]

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 arXiv   pre-print
Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.  ...  [227] Human activity chains generation Input-Output HMM + LSTM Adam First work that uses an RNN to generate human activity chains. Others Xu et al.  ...  Subsequently, an LSTM is designed for activity chain generation, given the labeled activity sequences.  ... 
arXiv:1803.04311v3 fatcat:awuvyviarvbr5kd5ilqndpfsde

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 IEEE Communications Surveys and Tutorials  
Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.  ...  [230] Human activity chains generation Input-Output HMM + LSTM Adam First work that uses an RNN to generate human activity chains. Others Xu et al.  ...  Subsequently, an LSTM is designed for activity chain generation, given the labeled activity sequences.  ... 
doi:10.1109/comst.2019.2904897 fatcat:xmmrndjbsfdetpa5ef5e3v4xda

2019 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 57

2019 IEEE Transactions on Geoscience and Remote Sensing  
., Geosynchronous SAR Tomography: Theory and First Experimental Verification Using Beidou IGSO Satellite; TGRS Sept. 2019 6591-6607 Hu, F., Wu, J., Chang, L., and Hanssen, R.F., Incorporating Temporary  ...  ., +, TGRS July 2019 4457-4469 Bayesian Inversion of Logging-While-Drilling Extra-Deep Directional Resistivity Measurements Using Parallel Tempering Markov Chain Monte Carlo Sampling.  ...  Yin, J., +, TGRS Dec. 2019 10362-10375 Drilling (geotechnical) Bayesian Inversion of Logging-While-Drilling Extra-Deep Directional Resistivity Measurements Using Parallel Tempering Markov Chain Monte Carlo  ... 
doi:10.1109/tgrs.2020.2967201 fatcat:kpfxoidv5bgcfo36zfsnxe4aj4

A survey on heterogeneous transfer learning

Oscar Day, Taghi M. Khoshgoftaar
2017 Journal of Big Data  
Models used in machine learning are trained from a series of examples comprised of features/attributes that are associated with a single label.  ...  When faced with unsupervised tasks, the class labels are not provided during training which can make the training process more challenging.  ...  The use of a Markov chain differs from TLRisk [37] as for CT-Learn the Markovian principles are used for the learning process while in TLRisk it is used to estimate parameters.  ... 
doi:10.1186/s40537-017-0089-0 fatcat:bpfjycwlkrawzdyyfv2ugle5cy

State of the Art of Audio- and Video-Based Solutions for AAL

Slavisa ALeksic, Michael Atanasov, Jean Calleja Agius, Kenneth Camilleri, Anto Čartolovni, Pau Climent-Pérez, Sara Colantonio, Stefania Cristina, Vladimir Despotovic, Hazım Kemal Ekenel, Ekrem Erakin, Francisco Florez-Revuelta (+27 others)
2022 Zenodo  
In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness.  ...  enable older, impaired or frail people to live independently and stay active longer in society.  ...  of video or the use of multiple viewpoints.  ... 
doi:10.5281/zenodo.6390708 fatcat:6qfwqd2v2rhe5iuu5zgz77ay4i

Deep Learning for Omnidirectional Vision: A Survey and New Perspectives [article]

Hao Ai, Zidong Cao, Jinjing Zhu, Haotian Bai, Yucheng Chen, Lin Wang
2022 arXiv   pre-print
[175] proposed a graph-based CNN model to estimate the fraction of the visual saliency via Markov Chains.  ...  Gaze Behavior Gaze following, also called gaze estimation, is related to detecting what people in the scene look at and are absorbed in.  ... 
arXiv:2205.10468v2 fatcat:73fks33oafa6zgxliccydvdbeq
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