Job offer

PhD position offering

Position and duration: PhD Thesis – 3 Years full time contract

Starting date: 1st of October 2016

Context :

This PhD thesis Subject is a part of an ongoing work between Mines ParisTech and PSA Peugeot Citroën Group, focused on car security. The context is the use of onboard visual digital information to inform the driver and increase his security. The digital information is acquired outside of the vehicle through the use of sensors. This is a confidential work, potentially leading to a patent, because of this, the scenario of use cannot be precisely described in this subject.

Objectives

There are two objectives in the thesis : 1) Reconstruct a real-time 3D view of the car environment, acquired from a fixed point of view on a moving car, and 2) Master the visual perception of that 3D data by a human, positioned within the car, and ensure the pertinence of its use for a given set of scenarios.

The point of view for the 3D reconstruction does not have to be a very wide angle view, but the visual refreshment of the 3D data has to deal with the specific constraints of car driving. Indeed, for high speeds, the processing time and delays can have a negative effect on the visual data presented to the driver and the algorithms for 3D reconstruction should account for spatial shifting effects.

One of the main purposes of this thesis is to perform a realistic but partial 3D environment reconstruction of the road environment, given the inherent constraints of the automotive field: speed of the vehicle, road visibility, etc. The aim is not in performing a complete 3D scene reconstruction, from a single viewpoint, but a real-time partial reconstruction with respect to the speed of the vehicle and the inherent perturbation phenomena: change in vehicle’s direction and other secondary motions. If a certain speed threshold is overpassed, unwanted effects can occur such as the processing time and the information rendering, therefore some strategies of image acquisition should be studied, in order to compensate these inconvenient situations. In a second phase, the emerging algorithms and technology should be validated from the perceptive point of view, by user experience tests. Use cases and tests will be defined for the system’s evaluation.

Description of work:

After a preliminary phase of the field’ state of the art, the PhD candidate should propose pertinent technical solutions of innovations over the existing technologies, able to respond to the challenges risen by the state of art. The second phase will be the algorithms implementation phase on the vehicle platform.

At the end, a definition phase of the realistic use case from the safety and security point of view will be analyzed, for the system assessment.

Finally, realistic use cases will be set up and evaluated. One central question as for the perceptive feasibility of the concept, is the question of visual behavior of the user. Indeed, it is unknown how the users will deal with the presence of visual information within the car, that is relative to events and objects that are outside of the car. Especially we will focus on accommodative behaviors, indeed, users may have two accommodative strategies: 1) switch between interior/exterior accommodation points or 2) keep an -outside of the car- accommodation strategy and use the digital visual information available within the car in their peripheral visual field. The open question being which, if any, one of these strategies is actually viable in the proposed interface.

Candidate profile

MSc Degree in Electrical Engineering, Computer Science or Physics.

Requirements:

Scientific knowledge in Virtual or Augmented Reality, Computer Vision and real-time computer programming.

• Job information:

The successful candidate will be enrolled in the Mines-ParisTech doctoral program and employee of the PSA Peugeot-Citroën Company.

• Working office/Laboratory :

Centre de Robotique / Mines ParisTech

60 boulevard Saint Michel

75272 Paris Cedex 06

http://caor-mines-paristech.fr/en/home/

• PhD Supervisors:

Director: Philippe Fuchs: philippe.fuchs@mines-paristech.fr

Scientific supervisor: Bogdan Stanciulescu: bogdan.stanciulescu@mines-paristech.fr

Scientific supervisor: Alexis Paljic: alexis.paljic@mines-paristech.fr

Administrative referent:

Mme Christine Vignaud

Phone: +33-(0)1 40 51 92 55

Email: christine.vignaud@mines-paristech.fr

Contact: bogdan.stanciulescu at mines-paristech.fr

Position and duration: Postdoctorate – 12 Months full time contract

Starting date: 1st of April 2016

Qualifications and skills: Applicants must have a PhD in the field of computer science, electrical engineering, physics, or any other related field. The candidates need to have a strong background in scene interpretation, particularly in the following fields: 3D environment reconstruction, SLAM, feature extraction, scene recognition, visual object detection. The applicants must have good communication skills, be able to work in a team environment and have fluent English skills. French language knowledge is a plus, but not compulsory.

The application must contain information of research background and work experience, including:

1. A motivation letter outlining background, experience and interest in the subject.
2. A detailed CV, including personal contact information and list of publications.

Applications must be submitted by e-mail to bogdan.stanciulescu at mines-paristech.fr with the subject: POSTDOCTORAL POSITION.

The Robotics Laboratory of Mines-ParisTech (CAOR) has developed extensive competences and tools in the field of computer vision and pattern recognition for real-time object detection and classification (people, vehicles, faces, etc). One of the CAOR’s algorithms has been internationally recognised as the 2^nd best Pascal VOC challenge 2006.

For its results in real-time object recognition and classification, the CAOR’s has been rewarded the Best Student Paper Award at the International Conference on Control, Automation, Robotics and Vision 2011, and again rewarded the International Joint Conference on Neural Networks 2011 object recognition challenge.

The postdoctoral associate could use the CAOR’s experience in real-time video processing, robust signature extraction from multiple images and machine learning.

Least but no last, the Robotics Lab has acquired a good experience in sensor data fusion for performing indoor SLAM. The Laboratory’s prototype « Corebots » has won 2 times out of 3 the DGA-ANR Carotte competition for mobile robots, by a precise 3D environment mapping and localisation.

SLAM laser mapping by Corebots prototype

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This entry in only available in french…

This entry is only available in french…