Sébastien Piérard

Orcid: 0000-0001-8076-1157

Affiliations:
  • Université de Liège, Belgium


According to our database1, Sébastien Piérard authored at least 26 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Mixture Domain Adaptation to Improve Semantic Segmentation in Real-World Surveillance.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, 2023

2022
An exploration of the performances achievable by combining unsupervised background subtraction algorithms.
CoRR, 2022

2020
Summarizing The Performances Of A Background Subtraction Algorithm Measured On Several Videos.
Proceedings of the IEEE International Conference on Image Processing, 2020

2018
LaBGen-P-Semantic: A First Step for Leveraging Semantic Segmentation in Background Generation.
J. Imaging, 2018

2017
Improving pedestrian detection using motion-guided filtering.
Pattern Recognit. Lett., 2017

LaBGen: A method based on motion detection for generating the background of a scene.
Pattern Recognit. Lett., 2017

Semantic background subtraction.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

A Two-Step Methodology for Human Pose Estimation Increasing the Accuracy and Reducing the Amount of Learning Samples Dramatically.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2017

2016
LaBGen-P: A pixel-level stationary background generation method based on LaBGen.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Leveraging Orientation Knowledge to Enhance Human Pose Estimation Methods.
Proceedings of the Articulated Motion and Deformable Objects, 2016

2015
Nonlinear Background Filter to Improve Pedestrian Detection.
Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2015 Workshops, 2015

A Perfect Estimation of a Background Image Does Not Lead to a Perfect Background Subtraction: Analysis of the Upper Bound on the Performance.
Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2015 Workshops, 2015

Simple Median-Based Method for Stationary Background Generation Using Background Subtraction Algorithms.
Proceedings of the New Trends in Image Analysis and Processing - ICIAP 2015 Workshops, 2015

2014
Design of a reliable processing pipeline for the non-intrusive measurement of feet trajectories with lasers.
Proceedings of the IEEE International Conference on Acoustics, 2014

Machine learning techniques to assess the performance of a gait analysis system.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
GAIMS: A Reliable Non-Intrusive Gait Measuring System.
ERCIM News, 2013

Efficient database pruning for large-scale cover song recognition.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
On the Human Pose Recovery based on a Single View.
Proceedings of the ICPRAM 2012, 2012

Estimation of Human Orientation based on Silhouettes and Machine Learning Principles.
Proceedings of the ICPRAM 2012, 2012

2011
Object Descriptors Based on a List of Rectangles: Method and Algorithm.
Proceedings of the Mathematical Morphology and Its Applications to Image and Signal Processing, 2011

A probabilistic pixel-based approach to detect humans in video streams.
Proceedings of the IEEE International Conference on Acoustics, 2011

A new jump edge detection method for 3D cameras.
Proceedings of the International Conference on 3D Imaging, 2011

Estimation of Human Orientation in Images Captured with a Range Camera.
Proceedings of the Advances Concepts for Intelligent Vision Systems, 2011

2010
A Virtual Curtain for the Detection of Humans and Access Control.
Proceedings of the Advanced Concepts for Intelligent Vision Systems, 2010

2009
Combining Color, Depth, and Motion for Video Segmentation.
Proceedings of the Computer Vision Systems, 2009


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