Category: Uncategorized

CeRVIM Webinar: A Comparative Study on Deep Learning based Semi-Supervised Video Anomaly Detection Methods. 

Mohammad Baradaran
Computer Vision and Systems Lab
Dép. de génie électrique et de génie informatique, Université Laval

June 21, 2021, 11h00

Résumé / Abstract
Nowadays, high-quality cameras are ubiquitous and a huge amount of video data are being recorded for different purposes (such as surveillance in public places, traffic control on highways, border control, studying human or animal behavior, production quality control, etc.). Analyzing this huge amount of data is beyond the capability of human operators, hence there is a need for intelligent systems to analyze video content and to detect events of interest automatically.

Video anomaly detection (abnormal event detection) is one of the hot research topics in computer vision today, as abnormal events contain a large amount of information. Anomalies are the events that deviate from the majority of observed events and are one of the main detection targets in surveillance systems and most of the suspicious events which take place belong to this group. For example, a car moving with the speed of 120 km/h on a road (with a maximum accepted speed of 120 km/h), on a snowy day while other cars drive slowly, would constitute an abnormal event.

In this presentation we will critically analyze state-of-the-art deep learning based semi-supervised video anomaly detection approaches, analyzing the strategies and pointing out their strong and weak points. These results are used and presented in our review paper. Moreover, the results of these experiments show the existing shortcomings in the field and provided the basis for our proposed method. Our proposed method will be presented in a forthcoming presentation.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter :
Annette.Schwerdtfeger@gel.ulaval.ca

CeRVIM Webinar: Multiple Cylinders Extraction from Organized Point Clouds. 

Saed Moradi
Computer Vision and Systems Lab
Dép. de génie électrique et de génie informatique, Université Laval

June 18, 2021, 11h00

Résumé / Abstract
Most man-made objects are composed of a few geometric primitives (GPs) such as spheres, cylinders, planes, ellipsoids, or cones. Thus, the object recognition problem can be considered as a geometric primitives extraction. Among the different geometric primitives, cylinders are the most frequently used GPs in real-world scenes. Therefore, cylinder detection and extraction are of great importance in 3D computer vision. Despite the rapid progress of cylinder detection algorithms, there are still two open problems in this area. First, a robust strategy is needed for the initial sample selection component of the cylinder extraction module. Second, detecting multiple cylinders simultaneously has not yet been investigated in depth. In this presentation, a robust solution is provided to address these problems.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter :
Annette.Schwerdtfeger@gel.ulaval.ca

Colloque REPARTI 2021: Wednesday, June 16, 2021, 9h00 – 11h00, on Zoom.*

A keynote presentation, followed by a series of short presentations, offered by researchers and students from the member institutions of REPARTI, will allow you to learn more about the research projects and initiatives carried out by REPARTI members. Here is the detailed program which includes the titles of all of the presentations:

Colloque REPARTI 2021 Program

*To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

Colloque CeRVIM 2021:  Friday, May 14, 2021, 9h30 – 11h30, on Zoom.*

A series of short presentations, offered by CeRVIM researchers and students, will allow you to learn more about the research projects and initiatives carried out by CeRVIM members. Here is the detailed program which includes the titles of all of the presentations:

Colloque CeRVIM 2021 Program

*To obtain the Zoom meeting web link, please contact:
Annette.Schwerdtfeger@gel.ulaval.ca

CeRVIM Webinar: Tirer profit des données en conception optique

Geoffroi Côté
Laboratoire de Recherche en Ingénierie Optique
Dép. de physique, de génie physique et d’optique, Université Laval

7 mai 2021, 11h00

Résumé / Abstract
En vision numérique, la modélisation de la caméra se fait habituellement au moyen d’un modèle optique approximatif, dit de premier ordre. L’analyse précise du comportement de tels systèmes optiques, de même que leur design, relève plutôt du domaine de la conception optique.

Dans cet exposé, je vais donner un bref aperçu de la conception optique, et expliquer comment le domaine peut tirer profit de méthodes axées sur les données. Je vais présenter comment l’apprentissage profond peut mener à la création d’outils concrets pour les concepteurs optiques, en combinant l’apprentissage supervisé habituel à un second signal d’entraînement basé sur le tracé de rayons optique. Finalement, je vais aborder une méthode pour intégrer la conception optique à la recherche en vision numérique.

La présentation sera donnée en français et les diapos seront en anglais.
The presentation will be given in French and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter:
Annette.Schwerdtfeger@gel.ulaval.ca

CeRVIM Webinar: Parallelism for Fast and Interactive Visualization of Big 3D Data

Duc Thien Luong
Laboratoire de Vision et Systèmes Numériques
Dép. de génie électrique et de génie informatique, Université Laval

30 avril 2021, 11h00

Résumé / Abstract
In recent years, the needs for 3D visualization have significantly increased in a wide range of applications: research, industry, entertainment, transport, security, even finance and investment. All of these applications involve processing and visualizing big data. There are 3 main obstacles in visualizing the big data. First, the computation workload of the 3D data can exceed the capacity of the commercial memory core (RAM). Secondly, the popular methodology in computing requires long computation times. Thirdly, interactivity between the users and the system is not preserved when we move the displaying screen because of the system delays. The proposed parallelism method is built to overcome each of these three problems. Although we use a powerful PC to develop this method, there is no requirement for special hardware. This method only focuses on programming methodology and software solutions. In addition, we maximize the use of GPU computing and parallel programming to reduce processing time.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter:
Annette.Schwerdtfeger@gel.ulaval.ca

CeRVIM Webinar: Covariance Based Differential Geometry Segmentation Techniques for Surface Representation Using a Vector Field Framework

Mana Eskandari
Laboratoire de Vision et Systèmes Numériques
Dép. de génie électrique et de génie informatique, Université Laval

16 avril 2021, 11h00

Résumé / Abstract
In this presentation, the concepts of differential geometry traditionally applied to the segmentation of range maps is revisited in the context of implicit surface representation of unorganized point clouds. We proposed an approach to demonstrate that it is possible to combine covariance-based differential geometry and implicit surface representation methods to perform the segmentation of an unorganized point cloud (and not just a range map) into different surface types. The advantages of combining covariance-based differential geometry and implicit surface representation are that the segmentation does not require surface fitting nor does it require that all points be processed, thus reducing computational complexity. The acquisition of the point cloud data is achieved with handheld scanners used in metrology applications.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter:
Annette.Schwerdtfeger@gel.ulaval.ca

REPARTI Webinars:

A journey on your brain highways: diffusion MRI and connectomics of the future
Maxime Descoteaux
Sherbrooke Connectivity Imaging Lab (http://scil.usherbrooke.ca/)
Dép. d’informatique, Université de Sherbrooke
February 16, 2021, 12:00 – 1:00 p.m.

Understanding the world behind the image
Jean-François Lalonde
Laboratoire de Vision et Systèmes Numériques (LVSN)
Dép. de génie électrique et de génie informatique, Université Laval
March 29, 2021, 12:00 – 1:00 p.m.

Ultrasound imaging: let’s talk
Catherine Laporte
Laboratoire de traitement de l’information en santé (LATIS)
École de technologie supérieure (ÉTS)
April 22, 2021, 12:00 – 1:00 p.m.

CeRVIM Webinar: Evaluation of Skid-Steering Kinematic Models for Subarctic Environments

Dominic Baril
Norlab (Northern Robotics Laboratory)
Dép. d’informatique et de génie logiciel, Université Laval

20 novembre 2020, 11h00

Résumé / Abstract
In subarctic and arctic areas, large and heavy skid-steered robots are preferred for their robustness and ability to operate on difficult terrain. State estimation, motion control and path planning for these robots rely on accurate odometry models based on wheel velocities. However, the state-of-the-art odometry models for skid-steer mobile robots (SSMRs) have usually been tested on relatively lightweight platforms. In this paper, we focus on how these models perform when deployed on a large and heavy (590 kg) SSMR. We collected more than 2 km of data on both snow and concrete. We compare the ideal differential-drive, extended differential-drive, radius-of-curvature-based, and full linear kinematic models commonly deployed for SSMRs. Each of the models is fine-tuned by searching their optimal parameters on both snow and concrete. We then discuss the relationship between the parameters, the model tuning, and the final accuracy of the models.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter:
Annette.Schwerdtfeger@gel.ulaval.ca

CeRVIM Webinar: Radio propagation models for differential GNSS based on dense point clouds

Vladimír Kubelka
Norlab (Northern Robotics Laboratory)
Dép. d’informatique et de génie logiciel, Université Laval

13 novembre 2020, 11h00

Résumé / Abstract
Accurate geolocation of mobile equipment operating in outdoor environments is an increasingly important question in robotics and automation. Modern geolocation systems, however, rely on the crucial ability for a mobile device to receive specific radio signals at all times. As such geolocation systems are increasingly deployed in harsh or difficult environments, for example, in the presence of tall buildings or dense forests, it becomes critical to predict how the environment will impact the propagation of these radio signals. We propose a signal propagation model that can determine what areas would be favorable for global navigation satellite system (GNSS) positioning, based on a prior three‐dimensional (3D) point cloud map of the environment. The model predicts both the number of usable satellites for a GNSS receiver and the strength of the reference radio signal used in the differential GNSS scenario. We take into account both signal occlusion and absorption mechanisms, given the geometry and density of the point cloud map. The design of the model is data-driven, based on experiments performed both at the university campus and in the Montmorency forest.

La présentation sera donnée en anglais et les diapos seront en anglais.
The presentation will be given in English and the slides will be in English.

To obtain the Zoom meeting web link, please contact:
Pour obtenir le lien d’accès pour la rencontre Zoom, SVP contacter:
Annette.Schwerdtfeger@gel.ulaval.ca