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[2019-09-27] Dr. Josiane Zerubia, INRIA, "Marked Point Processes For Object Detection and Tracking in High Resolution Images: Applications to Remote Sensing and Biology" (English Speech)

專題討論演講公告
Poster:Post date:2019-09-20
Title: Marked Point Processes For Object Detection and Tracking in High Resolution Images: Applications to Remote Sensing and Biology
Date: 2019-09-27 2:20pm-3:30pm
Location: R103, CSIE
Speaker: Dr. Josiane Zerubia, INRIA
Hosted by: Prof. Amy Lee
 
 

Abstract:

 
In this talk, we combine the methods from probability theory and stochastic geometry to put forward new solutions to the multiple object detection and tracking problem in high resolution remotely sensed image sequences. First, we present a spatial marked point process model to detect a pre-defined class of objects based on their visual and geometric characteristics. Then, we extend this model to the temporal domain and create a framework based on spatio-temporal marked point process models to jointly detect and track multiple objects in image sequences. We propose the use of simple parametric shapes to describe the appearance of these objects. We build new, dedicated energy based models consisting of several terms that take into account both the image evidence and physical constraints such as object dynamics, track persistence and mutual exclusion. We construct a suitable optimization scheme that allows us to find strong local minima of the proposed highly non-convex energy.

As the simulation of such models comes with a high computational cost, we turn our attention to the recent filter implementations for multiple object tracking, which are known to be less computationally expensive. We propose a hybrid sampler by combining the Kalman filter with the standard Reversible Jump MCMC. High performance computing techniques are also used to increase the computational efficiency of our method. We provide an in-depth analysis of the proposed framework based on standard multiple object tracking metrics and computational efficiency. This analysis yields a very good detection and tracking performance at the price of an increased complexity of the models. Exhaustive tests have been conducted both on high resolution satellite and microscopy image sequences.
 
 
Biography:
 
Josiane Zerubia has been a permanent research scientist at INRIA since 1989 and director of research since July 1995 (DR 1st class since 2002). She was head of the PASTIS remote sensing laboratory (INRIA Sophia-Antipolis) from mid-1995 to 1997 and of the Ariana research group (INRIA/CNRS/University of Nice), which worked on inverse problems in remote sensing and biological imaging, from 1998 to 2011. From 2012 to 2016, she was head of Ayin research group (INRIA-SAM) dedicated to models of spatio-temporal structure for high resolution image processing with a focus on remote sensing and skincare imaging. She has been professor (PR1) at SUPAERO (ISAE) in Toulouse since 1999.
 
Before that, she was with the Signal and Image Processing Institute of the University of Southern California (USC) in Los-Angeles as a postdoc. She also worked as a researcher for the LASSY (University of Nice/CNRS) from 1984 to 1988 and in the Research Laboratory of Hewlett Packard in France and in Palo-Alto (CA) from 1982 to 1984. She received the MSc degree from the Department of Electrical Engineering at ENSIEG, Grenoble, France in 1981, the Doctor of Engineering degree, her PhD and her ‘Habilitation’, in 1986, 1988, and 1994 respectively, all from the University of Nice Sophia-Antipolis, France.
 
She is a Fellow of both the IEEE (2003- ) and the EURASIP (2019), and was IEEE SP Society Distinguished Lecturer (2016-2017). She was a member of the IEEE IMDSP TC (SP Society) from 1997 till 2003, of the IEEE BISP TC (SP Society) from 2004 till 2012 and of the IVMSP TC (SP Society) from 2008 till 2013. She was associate editor of IEEE Trans. on IP from 1998 to 2002, area editor of IEEE Trans. on IP from 2003 to 2006, guest co-editor of a special issue of IEEE Trans. on PAMI in 2003, member of the editorial board of IJCV from 2004 till March 2013 and member-at-large of the Board of Governors of the IEEE SP Society from 2002 to 2004. She was also associate editor of the on-line resource « Earthzine » (IEEE CEO and GEOSS) from 2006 to mid-2018.   She has been a member of the editorial board of the French Society for Photogrammetry and Remote Sensing (SFPT) since 1998, of the Foundation and Trends in Signal Processing since 2007 and member-at-large of the Board of Governors of the SFPT since 2014. Finally, she has been a member of the editorial board of the IEEE Signal Processing Magazine since September 2018.
 
She was co-chair of two workshops on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR'01, Sophia Antipolis, France, and EMMCVPR'03, Lisbon, Portugal), co-chair of a workshop on Image Processing and Related Mathematical Fields (IPRM'02, Moscow, Russia), technical program chair of a workshop on Photogrammetry and Remote Sensing for Urban Areas (Marne La Vallée, France, 2003), co-chair of the special sessions at IEEE ICASSP 2006 (Toulouse, France) and IEEE ISBI 2008 (Paris, France), publicity chair of IEEE ICIP 2011 (Brussels, Belgium), tutorial co-chair of IEEE ICIP 2014 (Paris, France), general co-chair of the workshop EarthVision at IEEE CVPR 2015 (Boston, USA) and a member of the organizing committee and plenary talk co-chair of IEEE-EURASIP EUSIPCO 2015 (Nice, France). She also organized and chaired an international workshop on Stochastic Geometry and Big Data at Sophia Antipolis, France, in 2015. She was part of the organizing committees of the workshop EarthVision (co-chair) at IEEE CVPR 2017 (Honolulu, USA) and GRETSI 2017 symposium (Juan les Pins, France). She is scientific advisor and co-organizer of ISPRS 2020 congress (Nice, France) and technical co-chair of IEEE-EURASIP EUSIPCO 2021 (Dublin, Ireland).
 
Her main research interest is in image processing using probabilistic models. She also works on parameter estimation, statistical learning and optimization techniques, and artificial intelligence.

 
 
Last modification time:2019-09-20 AM 10:24

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