Zobrazeno 1 - 8 of 8 pro vyhledávání: '"Vahid Bastani"'
2
Online Nonparametric Bayesian Activity Mining and Analysis from Surveillance Video
Autor: Vahid Bastani, Carlo S. Regazzoni, Lucio Marcenaro
A method for online incremental mining of activity patterns from the surveillance video stream is presented in this paper. The framework consists of a learning block in which Dirichlet process mixture model is employed for the incremental clustering
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ce5aaa5c6854814f1230cc7532f2bd4
http://hdl.handle.net/11567/832442
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3
Image compression based on spatial redundancy removal and image inpainting
Autor: Mohammad Sadegh Helfroush, Vahid Bastani, Keyvan Kasiri
Publikováno v: Journal of Zhejiang University SCIENCE C. 11:92-100
We present an algorithm for image compression based on an image inpainting method. First the image regions that can be accurately recovered are located. Then, to reduce the data, information of such regions is removed. The remaining data besides esse
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8e85923be77dc2aae8cda90a8ff5ad69
https://doi.org/10.1631/jzus.c0910182
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4
Online pedestrian group walking event detection using spectral analysis of motion similarity graph
Autor: Damian Campo, Lucio Marcenaro, Carlo S. Regazzoni, Vahid Bastani
Publikováno v: 2015 12th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS).
A method for online identification of group of moving objects in the video is proposed in this paper. This method at each frame identifies group of tracked objects with similar local instantaneous motion pattern using spectral clustering on motion si
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d71d579412a0f9373509c308dca87c31
https://doi.org/10.1109/avss.2015.7301744
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5
Perception of emotions from crowd dynamics
Autor: Mirza Waqar Baig, Emilia I. Barakova, Mirza Sulman Baig, Vahid Bastani, Carlo S. Regazzoni, Matthias Rauterberg, Lucio Marcenaro
Publikováno v: DSP
2015 IEEE International Conference on Digital Signal Processing, DSP 2015, 21-24 July 2015, Singapore, 703-707
STARTPAGE=703;ENDPAGE=707;TITLE=2015 IEEE International Conference on Digital Signal Processing, DSP 2015, 21-24 July 2015, Singapore
Perceiving crowd emotions and understand the situation is vital to control the situations in surveillance applications. This paper introduces the evolution of methods for crowd emotion perception based on bio-inspired probabilistic models. The emotio
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05db1d8ac07e6a90a7af016c608a752a
https://doi.org/10.1109/icdsp.2015.7251966
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6
A particle filter based sequential trajectory classifier for behavior analysis in video surveillance
Autor: Carlo S. Regazzoni, Lucio Marcenaro, Vahid Bastani
Publikováno v: ICIP
The problem of behavior assessment in video surveillance is approached using trajectory classification. Lagrangian state dynamic is used for probabilistic modeling of trajectory patterns and an off-line parameter learning method for the model is prop
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15d1222886935b09163d3b2bf0b527cb
http://hdl.handle.net/11567/840344
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7
Unsupervised Trajectory Pattern Classification Using Hierarchical Dirichlet Process Mixture Hidden Markov Model
Autor: Lucio Marcenaro, Carlo S. Regazzoni, Vahid Bastani
Publikováno v: MLSP
In this paper we present a trajectory clustering method based on nonparametric Bayesian approach proposed for analyzing dynamic systems. Our method uses a modified hierarchical Dirichlet process-hidden Markov model in order to learn trajectory patter
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7a136c09b8c7e4645300532116110f7
https://hdl.handle.net/11567/774037
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8
Online Bayesian Learning and Classification of Ship-to-Ship Interactions for Port Safety
Autor: Carlo S. Regazzoni, Lucio Marcenaro, Francesco Castaldo, Francesco Palmieri, Vahid Bastani
Publikováno v: AVSS
Interaction analysis of ships mooring and maneuvering in harbors is pursued in this paper by using Bayesian probabilistic models. A number of ship-to-ship interactions are deduced from the navigation rules in port areas, and then used to train differ
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7277ff7b318f75f235585553f8bf5d5f
https://hdl.handle.net/11567/811608
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