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Nonparametric Bayesian attentive video analysis

Giuseppe Boccignone
2008 Pattern Recognition (ICPR), Proceedings of the International Conference on  
We address the problem of object-based visual attention from a Bayesian standpoint.  ...  To this end we propose a framework relying on nonparametric Bayesian techniques, namely variational inference on a mixture of Dirichlet processes.  ...  In this respect, variational techniques have proven to be a viable tool for video analysis.  ... 
doi:10.1109/icpr.2008.4760948 dblp:conf/icpr/Boccignone08 fatcat:lsmqkxnmifczlc3lpdg3th6nla

Table of contents

2019 IEEE transactions on circuits and systems for video technology (Print)  
Zhao 787 ML-HDP: A Hierarchical Bayesian Nonparametric Model for Recognizing Human Actions in Video .................. ....................................................................... N.  ...  Image/Video Analysis and Computer Vision Aggregation of Rich Depth-Aware Features in a Modified Stacked Generalization Model for Single Image Depth Estimation ............................ H.  ... 
doi:10.1109/tcsvt.2019.2900780 fatcat:vntdkc4xtrbv5e4zwt3hxrzu3u

Interactive browsing system for anomaly video surveillance

Tien-Vu Nguyen, Dinh Phung, S. Gupta, S. Venkatesh
2013 2013 IEEE Eighth International Conference on Intelligent Sensors, Sensor Networks and Information Processing  
Introducing a novel way to compute rare motion patterns, we estimate latent factors of foreground motion patterns through Bayesian Nonparametric Factor analysis.  ...  We demonstrate the system on a public video data set, showing key aspects of the browsing paradigm.  ...  Since the number of latent factors is unknown in advance, we employ recent advances in Bayesian nonparametric factor analysis.  ... 
doi:10.1109/issnip.2013.6529821 dblp:conf/issnip/NguyenPGV13 fatcat:a6m6smxoljevdfrag5snjuocoy

Nonparametric Hierarchical Bayesian Models for Positive Data Clustering Based on Inverted Dirichlet-Based Distributions

Wentao Fan, Nizar bouguila
2019 IEEE Access  
INDEX TERMS Clustering, mixture models, inverted Dirichlet, nonparametric Bayesian model, stochastic variational inference.  ...  In this paper, we propose nonparametric hierarchical Bayesian models based on two inverted Dirichlet-based distributions and Pitman-Yor process for positive data features clustering.  ...  It is a critical problem in video analysis and has been applied as an interest detector 83608 VOLUME 7, 2019 in various higher level problems, such as video surveillance, human motion analysis, object  ... 
doi:10.1109/access.2019.2924651 fatcat:6at4tmwtlzeuxfrbhfher7uyui

Anomaly Detection in Unstructured Environments using Bayesian Nonparametric Scene Modeling [article]

Yogesh Girdhar, Walter Cho, Matthew Campbell, Jesus Pineda, Elizabeth Clarke, Hanumant Singh
2016 arXiv   pre-print
This paper explores the use of a Bayesian non-parametric topic modeling technique for the purpose of anomaly detection in video data. We present results from two experiments.  ...  In the second dataset, consisting of video data from a static seafloor camera capturing images of a busy coral reef, the proposed technique was able to detect all three instances of an underwater vehicle  ...  The Bayesian nonparametric nature of the approach insures that the anomaly models adapts automatically to the data, without requiring careful tuning of the hyper-parameters.  ... 
arXiv:1509.07979v2 fatcat:oi2gu7k5mjc57f2nlj67i7qdwu

GP CaKe: Effective brain connectivity with causal kernels [article]

Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris
2017 arXiv   pre-print
The causal kernels are learned nonparametrically using Gaussian process regression, yielding an efficient framework for causal inference.  ...  Here we propose to model this causal interaction using integro-differential equations and causal kernels that allow for a rich analysis of effective connectivity.  ...  Effective connectivity using MEG for three conditions: I. resting state (R), II. attention to video stream (V) and III. attention to audio stream (A).  ... 
arXiv:1705.05603v1 fatcat:6k77dlbecfhghackq4uqe4ucru

[Invited papers] Supervised Nonparametric Multimodal Topic Models for Multi-class Video Classification

Jianfei Xue, Koji Eguchi
2019 ITE Transactions on Media Technology and Applications  
Nonparametric topic models such as hierarchical Dirichlet processes (HDP) have been attracting more and more attentions for multimedia data analysis.  ...  video data are modeled as a predictor of video class.  ...  On this point, HDP and Bayesian nonparametric topic models are more flexible and effective than LDA and Bayesian parametric topic models.  ... 
doi:10.3169/mta.7.80 fatcat:fe6wbherr5a6tc5m4ww2nvnlyu

A Survey on Bayesian Nonparametric Learning

Junyu Xuan, Jie Lu, Guangquan Zhang
2019 ACM Computing Surveys  
Due to the great success of this work, computer scientists began to pay attention to Bayesian nonparametrics, giving rise to BNL.  ...  DEFINITIONS One closely related definition of Bayesian nonparametrics is given by statisticians as Definition 1 (Bayesian nonparametrics [88]).  ...  Thus, learning out a hierarchical structure from plain data has attracted a great deal of attention from researchers in the Bayesian nonparametric field.  ... 
doi:10.1145/3291044 fatcat:aytdnsnrfvfnti5i64ne4icenu

Video Modeling by Spatio-Temporal Resampling and Bayesian Fusion

Yunfei Zheng, Xin Li
2007 2007 IEEE International Conference on Image Processing  
In this paper, we propose an empirical Bayesian approach toward video modeling and demonstrate its application in multiframe image restoration.  ...  When combined with STALL model, we show how to probabilistically combine the linear regression results of resampled video signals under a Bayesian framework.  ...  In recent years, statistical modeling of video signals without explicit motion estimation have received increasingly more attention.  ... 
doi:10.1109/icip.2007.4379607 dblp:conf/icip/ZhengL07 fatcat:pjlubetrj5bjff7n53sbeof4je

An Overview of Bayesian Methods for Neural Spike Train Analysis

Zhe Chen
2013 Computational Intelligence and Neuroscience  
Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels.  ...  Some research challenges and opportunities for neural spike train analysis are discussed.  ...  In recent years, cutting-edge Bayesian methods have gained increasing attention in the analysis of neural data and neural spike trains.  ... 
doi:10.1155/2013/251905 pmid:24348527 pmcid:PMC3855941 fatcat:nkst6mt3sfcqheuxheda3wq4wq

A Review Of Attention Models In Image Protrusion And Object Detection

Seyyed Mohammad Reza Hashemi, Ali Broumandnia
2015 Journal of Mathematics and Computer Science  
The present article surveys the primary concepts of visual attention, implemented in cognitive, Bayesian network, decision theories, and information theory in a computational perspective.  ...  Modelling in visual attention especially the stimulus-driven one, i.e. saliency-based attention, has been a very active research field during the recent 25 years.  ...  Li et al presented a Bayesian multi-tasking learning framework for visual attention in videos.  ... 
doi:10.22436/jmcs.015.04.02 fatcat:uldnv2mhoncxndcsowztrxcrte

Manipulation Pattern Discovery: A Nonparametric Bayesian Approach

Bingbing Ni, Pierre Moulin
2013 2013 IEEE International Conference on Computer Vision  
We therefore propose a nonparametric Bayesian method that adopts a hierarchical Dirichlet process prior to learn representative manipulation (motion) patterns in an unsupervised manner.  ...  Wang et. al [18] used hierarchical nonparametric Bayesian models for crowd analysis.  ...  While their work only focuses on traffic (crowd behavior) analysis, we propose to use nonparametric Bayesian for discovering representative object manipulation patterns. Packer et al.  ... 
doi:10.1109/iccv.2013.172 dblp:conf/iccv/NiM13 fatcat:6yzwvamm2bgwrfjbblipdarhqq

Author Index

2010 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition  
Hierarchical Bayesian Model for Functional Brain Parcellation Hu, Han Trajectory Matching from Unsynchronized Videos Hu, Weiming Use Bin-Ratio Information for Category and Scene Classification Workshop  ...  Video Analysis Sensor Units for Wide Area Surveillance Lee, Sang Uk Learning Full Pairwise Affinities for Spectral Segmentation Author Index file:///L:/JOBS/45636%20IEEE%20CVPR/45636-DVD-HTML-Search  ... 
doi:10.1109/cvpr.2010.5539913 fatcat:y6m5knstrzfyfin6jzusc42p54

Nonparametric bottom-up saliency detection by self-resemblance

Hae Jong Seo, P. Milanfar
2009 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
Analysis of visual attention is considered a very important component in the human vision system because of a wide range of applications such as object detection, predicting human eye fixation, video summarization  ...  Itti and Baldi [12] proposed so-called "Bayesian Surprise" and extended it to the video case [11] .  ... 
doi:10.1109/cvpr.2009.5204207 fatcat:7uh5ub6645a6xbakjhvs2xvjy4

Nonparametric bottom-up saliency detection by self-resemblance

Hae Jong Seo, Peyman Milanfar
2009 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
Analysis of visual attention is considered a very important component in the human vision system because of a wide range of applications such as object detection, predicting human eye fixation, video summarization  ...  Itti and Baldi [12] proposed so-called "Bayesian Surprise" and extended it to the video case [11] .  ... 
doi:10.1109/cvprw.2009.5204207 dblp:conf/cvpr/SeoM09 fatcat:vehxm6yxuzclzgrpnyjem4vsye
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