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Patrick Bouthemy - IEEE Xplore Author Profile
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Patrick Bouthemy

Also published under: P. Bouthemy

Publications
110
Citations
2,655
Publications by Year
19842024
Co-Authors:
Show All Co-Authors (115)
Image of author Patrick Bouthemy

Patrick Bouthemy

Also published under: P. Bouthemy

Affiliation

Inria, Rennes, France

Publication Topics

Biography

Patrick Bouthemy graduated from Télécom Paris, in 1980, and received the Ph.D degree from the University of Rennes 1, France, in 1982. From December 1982 to February 1984, he was with INRS-Télécommunications, Montreal, Canada, in the Department of Visual Communications. Since April 1984, he has been with Inria. From 1997 to 2007, he headed the Vista research group. From July 2007 to September 2011, he was Director of the Inria research centre in Rennes. Since October 2011, he has joined the Serpico research group. Since April 2014, he has been heading the CominLabs excellence laboratory. His main research interests are statistical approaches for image sequence analysis; image sequence denoising; motion detection, segmentation and estimation...
Publications
110
Citations
2,655
Publications by Year
19842024
Co-Authors:
Show All Co-Authors (115)
Author's Published Works

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Efficient local correlation volume for unsupervised optical flow estimation on small moving objects in large satellite images

Sarra Khairi;Etienne Meunier;Renaud Fraisse;Patrick Bouthemy

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2024 | Conference Paper |
With the advent of deep learning methods, performance and efficiency of optical flow estimation has significantly increased, especially for supervised models. However, they do not generalize well to more specific data involving small moving objects in large images, such as high-resolution aerial or satellite sequences. In addition, annotation and realistic simulation are difficult for these conten...Show More

Efficient local correlation volume for unsupervised optical flow estimation on small moving objects in large satellite images

Sarra Khairi;Etienne Meunier;Renaud Fraisse;Patrick Bouthemy

Year: 2024 | Conference Paper |

Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple Motions

Etienne Meunier;Patrick Bouthemy

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Motion segmentation is one of the main tasks in computer vision and is relevant for many applications. The optical flow (OF) is the input generally used to segment every frame of a video sequence into regions of coherent motion. Temporal consistency is a key feature of motion segmentation, but it is often neglected. In this paper, we propose an original unsupervised spatiotemporal framework for mo...Show More

Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple Motions

Etienne Meunier;Patrick Bouthemy

Year: 2023 | Conference Paper |

EM-Driven Unsupervised Learning for Efficient Motion Segmentation

Etienne Meunier;Anaïs Badoual;Patrick Bouthemy

IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2023 | Volume: 45, Issue: 4 | Journal Article |
Cited by: Papers (9)
In this paper, we present a CNN-based fully unsupervised method for motion segmentation from optical flow. We assume that the input optical flow can be represented as a piecewise set of parametric motion models, typically, affine or quadratic motion models. The core idea of our work is to leverage the Expectation-Maximization (EM) framework in order to design in a well-founded manner a loss functi...Show More

EM-Driven Unsupervised Learning for Efficient Motion Segmentation

Etienne Meunier;Anaïs Badoual;Patrick Bouthemy

Year: 2023 | Volume: 45, Issue: 4 | Journal Article |

Trajectory Saliency Detection Using Consistency-Oriented Latent Codes From a Recurrent Auto-Encoder

Léo Maczyta;Patrick Bouthemy;Olivier Le Meur

IEEE Transactions on Circuits and Systems for Video Technology
Year: 2022 | Volume: 32, Issue: 4 | Journal Article |
Cited by: Papers (1)
In this paper, we are concerned with the detection of progressive dynamic saliency from video sequences. More precisely, we are interested in saliency related to motion and likely to appear progressively over time. It can be relevant to trigger alarms, to dedicate additional processing or to detect specific events. Trajectories represent the best way to support progressive dynamic saliency detecti...Show More

Trajectory Saliency Detection Using Consistency-Oriented Latent Codes From a Recurrent Auto-Encoder

Léo Maczyta;Patrick Bouthemy;Olivier Le Meur

Year: 2022 | Volume: 32, Issue: 4 | Journal Article |

3D Optical Flow Estimation Combining 3D Census Signature and Total Variation Regularization

Sandeep Manandhar;Patrick Bouthemy;Eric Welf;Philippe Roudot;Charles Kervrann

2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)
Year: 2020 | Conference Paper |
We present a 3D optical flow method for 3D fluorescence image sequences which preserves discontinuities in the computed flow field. We propose to minimize an energy function composed of a linearized 3D Census signature-based data term and a total variational (TV) regularizer. To demonstrate the efficiency of our method, we have applied it to real sequences depicting collagen network, where the mot...Show More

3D Optical Flow Estimation Combining 3D Census Signature and Total Variation Regularization

Sandeep Manandhar;Patrick Bouthemy;Eric Welf;Philippe Roudot;Charles Kervrann

Year: 2020 | Conference Paper |

ROAM: A Rich Object Appearance Model with Application to Rotoscoping

Juan-Manuel Pérez-Rúa;Ondrej Miksik;Tomas Crivelli;Patrick Bouthemy;Philip H. S. Torr;Patrick Pérez

IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2020 | Volume: 42, Issue: 8 | Journal Article |
Cited by: Papers (2)
Rotoscoping, the detailed delineation of scene elements through a video shot, is a painstaking task of tremendous importance in professional post-production pipelines. While pixel-wise segmentation techniques can help for this task, professional rotoscoping tools rely on parametric curves that offer the artists a much better interactive control on the definition, editing and manipulation of the se...Show More

ROAM: A Rich Object Appearance Model with Application to Rotoscoping

Juan-Manuel Pérez-Rúa;Ondrej Miksik;Tomas Crivelli;Patrick Bouthemy;Philip H. S. Torr;Patrick Pérez

Year: 2020 | Volume: 42, Issue: 8 | Journal Article |

Unsupervised Motion Saliency Map Estimation Based On Optical Flow Inpainting

L. Maczyta;P. Bouthemy;O. Le Meur

2019 IEEE International Conference on Image Processing (ICIP)
Year: 2019 | Conference Paper |
Cited by: Papers (4)
The paper addresses the problem of motion saliency in videos, that is, identifying regions that undergo motion departing from its context. We propose a new unsupervised paradigm to compute motion saliency maps. The key ingredient is the flow inpainting stage. Candidate regions are determined from the optical flow boundaries. The residual flow in these regions is given by the difference between the...Show More

Unsupervised Motion Saliency Map Estimation Based On Optical Flow Inpainting

L. Maczyta;P. Bouthemy;O. Le Meur

Year: 2019 | Conference Paper |

Intensity-based matching and registration for 3D correlative microscopy with large discrepancies

Bertha Mayela Toledo Acosta;Xavier Heiligenstein;Grégoire Malandain;Patrick Bouthemy

2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
Year: 2018 | Conference Paper |
Cited by: Papers (2)
Correlative microscopy, especially light and electron microscopy (CLEM), enables the study of cells and subcellular elements in complementary ways, provided a reliable registration between images is efficiently achievable. We propose a general automatic registration method. Due to large discrepancies in appearance, field-of-view, resolution and position, a pre-alignment stage is required before an...Show More

Intensity-based matching and registration for 3D correlative microscopy with large discrepancies

Bertha Mayela Toledo Acosta;Xavier Heiligenstein;Grégoire Malandain;Patrick Bouthemy

Year: 2018 | Conference Paper |

A sparse-to-dense method for 3D optical flow estimation in 3D light-microscopy image sequences

Sandeep Manandhar;Patrick Bouthemy;Erik Welf;Philippe Roudot;Charles Kervrann

2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
We present a two-stage 3D optical flow estimation method for light microscopy image volumes. The method takes a pair of light microscopy image volumes as input, segments the 2D slices of the source volume in superpixels and sparsely estimates the 3D displacement vectors in the volume pair. A weighted interpolation is then introduced to get a dense 3D flow field. Edges and motion boundaries are con...Show More

A sparse-to-dense method for 3D optical flow estimation in 3D light-microscopy image sequences

Sandeep Manandhar;Patrick Bouthemy;Erik Welf;Philippe Roudot;Charles Kervrann

Year: 2018 | Conference Paper |

Multi-scale spot segmentation with selection of image scales

Bertha Mayela Toledo Acosta;Antoine Basset;Patrick Bouthemy;Charles Kervrann

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2017 | Conference Paper |
Detecting spot-like objects of different sizes in images is needed in many applications. Multiple image scales must then be handled for reliable spot segmentation. We define an original criterion based on the a contrario approach and the LoG scale-space framework to automatically select the meaningful scales. We then design a coarse-to-fine multi-scale spot segmentation scheme involving a locally ...Show More

Multi-scale spot segmentation with selection of image scales

Bertha Mayela Toledo Acosta;Antoine Basset;Patrick Bouthemy;Charles Kervrann

Year: 2017 | Conference Paper |

Determining Occlusions from Space and Time Image Reconstructions

Juan-Manuel Pérez-Rúa;Tomas Crivelli;Patrick Bouthemy;Patrick Pérez

2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2016 | Conference Paper |
Cited by: Papers (7)
The problem of localizing occlusions between consecutive frames of a video is important but rarely tackled on its own. In most works, it is tightly interleaved with the computation of accurate optical flows, which leads to a delicate chicken-and-egg problem. With this in mind, we propose a novel approach to occlusion detection where visibility or not of a point in next frame is formulated in terms...Show More

Determining Occlusions from Space and Time Image Reconstructions

Juan-Manuel Pérez-Rúa;Tomas Crivelli;Patrick Bouthemy;Patrick Pérez

Year: 2016 | Conference Paper |

Robust selection of parametric motion models in image sequences

Patrick Bouthemy;Bertha Mayela Toledo Acosta;Bernard Delyon

2016 IEEE International Conference on Image Processing (ICIP)
Year: 2016 | Conference Paper |
Cited by: Papers (1)
Parametric motion models are commonly used in image sequence analysis for different tasks. A robust estimation framework is usually required to reliably compute the motion model. The choice of the right model is also important. However, dealing simultaneously with both issues remains an open question. We propose a robust motion model selection method with two variants, which relies on the Fisher t...Show More

Robust selection of parametric motion models in image sequences

Patrick Bouthemy;Bertha Mayela Toledo Acosta;Bernard Delyon

Year: 2016 | Conference Paper |

Hierarchical motion decomposition for dynamic scene parsing

Juan-Manuel Pérez-Rúa;Tomas Crivelli;Patrick Pérez;Patrick Bouthemy

2016 IEEE International Conference on Image Processing (ICIP)
Year: 2016 | Conference Paper |
A number of applications in video analysis rely on a per-frame motion segmentation of the scene as key preprocessing step. Moreover, different settings in video production require extracting segmentation masks of multiple moving objects and object parts in a hierarchical fashion. In order to tackle this problem, we propose to analyze and exploit the compositional structure of scene motion to provi...Show More

Hierarchical motion decomposition for dynamic scene parsing

Juan-Manuel Pérez-Rúa;Tomas Crivelli;Patrick Pérez;Patrick Bouthemy

Year: 2016 | Conference Paper |

A common image representation and a patch-based search for correlative light-electron-microscopy (CLEM) registration

Bertha Mayela Toledo Acosta;Patrick Bouthemy;Charles Kervrann

2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Year: 2016 | Conference Paper |
Cited by: Papers (3)
Correlative light-electron microscopy (CLEM) enables to relate dynamics (or functions) with structure for a better understanding of cell mechanisms. However, the LM and EM images are of very different size, spatial resolution, field of view, and appearance. Registration of LM and EM modalities is then a timely, important but difficult open problem, which still requires some manual assistance. We h...Show More

A common image representation and a patch-based search for correlative light-electron-microscopy (CLEM) registration

Bertha Mayela Toledo Acosta;Patrick Bouthemy;Charles Kervrann

Year: 2016 | Conference Paper |

Detection and estimation of membrane diffusion during exocytosis in TIRFM image sequences

A. Basset;P. Bouthemy;J. Boulanger;F. Waharte;C. Kervrann;J. Salamero

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
Assessing the dynamics of plasma membrane diffusion processes in live cell fluorescence microscopy is of paramount interest to understand cell mechanisms. We propose a new method to detect vesicle fusion events, and estimate the associated diffusion coefficients in image sequences of total internal reflection fluorescence microscopy (TIRFM). In contrast to usual approaches, a diffusion coefficient...Show More

Detection and estimation of membrane diffusion during exocytosis in TIRFM image sequences

A. Basset;P. Bouthemy;J. Boulanger;F. Waharte;C. Kervrann;J. Salamero

Year: 2015 | Conference Paper |

Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images

Antoine Basset;Jérôme Boulanger;Jean Salamero;Patrick Bouthemy;Charles Kervrann

IEEE Transactions on Image Processing
Year: 2015 | Volume: 24, Issue: 11 | Journal Article |
Cited by: Papers (30)
Accurately detecting subcellular particles in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking, or classification. Our primary goal is to segment vesicles likely to share nearly the same size in fluorescence microscopy images. Our method termed adaptive thresholding of Laplacian of Gaussian (LoG) images with autoselected scale (ATLAS) auto...Show More

Adaptive Spot Detection With Optimal Scale Selection in Fluorescence Microscopy Images

Antoine Basset;Jérôme Boulanger;Jean Salamero;Patrick Bouthemy;Charles Kervrann

Year: 2015 | Volume: 24, Issue: 11 | Journal Article |

Background Fluorescence Estimation and Vesicle Segmentation in Live Cell Imaging With Conditional Random Fields

Thierry Pécot;Patrick Bouthemy;Jérôme Boulanger;Anatole Chessel;Sabine Bardin;Jean Salamero;Charles Kervrann

IEEE Transactions on Image Processing
Year: 2015 | Volume: 24, Issue: 2 | Journal Article |
Cited by: Papers (21)
Image analysis applied to fluorescence live cell microscopy has become a key tool in molecular biology since it enables to characterize biological processes in space and time at the subcellular level. In fluorescence microscopy imaging, the moving tagged structures of interest, such as vesicles, appear as bright spots over a static or nonstatic background. In this paper, we consider the problem of...Show More

Background Fluorescence Estimation and Vesicle Segmentation in Live Cell Imaging With Conditional Random Fields

Thierry Pécot;Patrick Bouthemy;Jérôme Boulanger;Anatole Chessel;Sabine Bardin;Jean Salamero;Charles Kervrann

Year: 2015 | Volume: 24, Issue: 2 | Journal Article |

Recovery of motion patterns and dominant paths in videos of crowded scenes

Antoine Basset;Patrick Bouthemy;Charles Kervrann

2014 IEEE International Conference on Image Processing (ICIP)
Year: 2014 | Conference Paper |
Cited by: Papers (4)
Assessing crowd behaviors from videos is a difficult task while of interest in many applications. We have defined a novel approach which identifies from two successive frames only, crowd behaviors expressed by simple image motion patterns. It relies on the estimation of a collection of sub-affine motion models in the image, a local motion classification based on a penalized likelihood criterion, a...Show More

Recovery of motion patterns and dominant paths in videos of crowded scenes

Antoine Basset;Patrick Bouthemy;Charles Kervrann

Year: 2014 | Conference Paper |

Action Localization with Tubelets from Motion

Mihir Jain;Jan Van Gemert;Hervé Jégou;Patrick Bouthemy;Cees G.M. Snoek

2014 IEEE Conference on Computer Vision and Pattern Recognition
Year: 2014 | Conference Paper |
This paper considers the problem of action localization, where the objective is to determine when and where certain actions appear. We introduce a sampling strategy to produce 2D+t sequences of bounding boxes, called tubelets. Compared to state-of-the-art alternatives, this drastically reduces the number of hypotheses that are likely to include the action of interest. Our method is inspired by a r...Show More

Action Localization with Tubelets from Motion

Mihir Jain;Jan Van Gemert;Hervé Jégou;Patrick Bouthemy;Cees G.M. Snoek

Year: 2014 | Conference Paper |

Localization and classification of membrane dynamics in TIRF microscopy image sequences

Antoine Basset;Patrick Bouthemy;Jérôme Boulanger;Jean Salamero;Charles Kervrann

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (3)
The detection of proteins and the classification of their temporal behaviors in live cell fluorescence microscopy are of utmost importance to understand cell mechanisms. In this paper, we aim at locating and recognizing temporal events in TIRF microscopy image sequences related to membrane dynamics. After segmenting the time-varying vesicles in the image, we exploit space-time information extracte...Show More

Localization and classification of membrane dynamics in TIRF microscopy image sequences

Antoine Basset;Patrick Bouthemy;Jérôme Boulanger;Jean Salamero;Charles Kervrann

Year: 2014 | Conference Paper |

Estimation of the flow of particles within a partition of the image domain in fluorescence video-microscopy

Thierry Pécot;Jérôme Boulanger;Charles Kervrann;Patrick Bouthemy;Jean Salamero

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (3)
Automatic analysis of the dynamic content in fluorescence video-microscopy is crucial for understanding molecular mechanisms involved in cell functions. In this paper, we propose an original approach for analyzing particle trafficking in these sequences. Instead of individually tracking every particle, we estimate the particle flows between predefined regions. This approach allows us to process im...Show More

Estimation of the flow of particles within a partition of the image domain in fluorescence video-microscopy

Thierry Pécot;Jérôme Boulanger;Charles Kervrann;Patrick Bouthemy;Jean Salamero

Year: 2014 | Conference Paper |

SLT-LoG: A vesicle segmentation method with automatic scale selection and local thresholding applied to TIRF microscopy

Antoine Basset;Jérôme Boulanger;Patrick Bouthemy;Charles Kervrann;Jean Salamero

2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI)
Year: 2014 | Conference Paper |
Cited by: Papers (7)
Accurately detecting cellular structures in fluorescence microscopy is of primary interest for further quantitative analysis such as counting, tracking or classification. We aim at segmenting vesicles in TIRF images. The optimal segmentation scale is automatically selected, relying on a multiscale feature detection stage, and the segmentation consists in thresholding the Laplacian of Gaussian of t...Show More

SLT-LoG: A vesicle segmentation method with automatic scale selection and local thresholding applied to TIRF microscopy

Antoine Basset;Jérôme Boulanger;Patrick Bouthemy;Charles Kervrann;Jean Salamero

Year: 2014 | Conference Paper |

Frame-by-frame crowd motion classification from affine motion models

Antoine Basset;Patrick Bouthemy;Charles Kervrann

2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance
Year: 2013 | Conference Paper |
Cited by: Papers (2)
Recognizing dynamic behaviors of dense crowds in videos is of great interest in many surveillance applications. In contrast to most existing methods which are based on trajectories or tracklets, our approach for crowd motion analysis provides a crowd motion classification on a frame-by-frame and pixel-wise basis. Indeed, we only compute affine motion models from pairs of two consecutive video imag...Show More

Frame-by-frame crowd motion classification from affine motion models

Antoine Basset;Patrick Bouthemy;Charles Kervrann

Year: 2013 | Conference Paper |

Better Exploiting Motion for Better Action Recognition

Mihir Jain;Hervé Jégou;Patrick Bouthemy

2013 IEEE Conference on Computer Vision and Pattern Recognition
Year: 2013 | Conference Paper |
Several recent works on action recognition have attested the importance of explicitly integrating motion characteristics in the video description. This paper establishes that adequately decomposing visual motion into dominant and residual motions, both in the extraction of the space-time trajectories and for the computation of descriptors, significantly improves action recognition algorithms. Then...Show More

Better Exploiting Motion for Better Action Recognition

Mihir Jain;Hervé Jégou;Patrick Bouthemy

Year: 2013 | Conference Paper |

Aggregation of patch-based estimations for illumination-invariant optical flow in live cell imaging

Denis Fortun;Patrick Bouthemy;Perrine Paul-Gilloteaux;Charles Kervrann

2013 IEEE 10th International Symposium on Biomedical Imaging
Year: 2013 | Conference Paper |
Cited by: Papers (4)
Live cell image sequences provide a large variety of challenging situations for motion estimation. We present a novel optical flow estimation method based on a two-stage aggregation framework and designed to handle this diversity of issues. First, semi-local candidates are estimated with a combination of patch correspondences and illumination-invariant affine motion estimations. Then, one candidat...Show More

Aggregation of patch-based estimations for illumination-invariant optical flow in live cell imaging

Denis Fortun;Patrick Bouthemy;Perrine Paul-Gilloteaux;Charles Kervrann

Year: 2013 | Conference Paper |

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