What is Where? Visual Understanding for Autonomous Cars

Date

2020-01-09 11:36

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Volume Title

Publisher

Cranfield University

Department

Type

Presentation

ISSN

Format

Citation

Grenier, Amélie (2020). What is Where? Visual Understanding for Autonomous Cars. Cranfield Online Research Data (CORD). Presentation. https://doi.org/10.17862/cranfield.rd.11558580.v1

Abstract

Autonomous driving has been rapidly evolving for the last few years and there is a lot of fervour in increasing the intelligence of these vehicles. One key aspect of a self-driving car is its ability to sense the environment in order to be aware of its surroundings and consecutively take better decisions.While the right combination of sensors is widely debated, my research interest lies in using computer vision and machine learning techniques to detect, localise and recognise surrounding entities. My talk will describe my research objectives and the expected outcome. It will address some of the encountered challenges, resulting from the urban traffic environment context and my sensor choice. It will include a mention of the algorithms that I have tested so far and those currently in development. You will have a glance at some of the questions that researchers are presently trying to answer in this interdisciplinary field.

Description

Software Description

Software Language

Github

Keywords

'Scene understanding', 'Machine learning', 'Autonomous driving', 'DSDS19', 'DSDS19 3MT', 'Autonomous Vehicles', 'Computer Vision', 'Knowledge Representation and Machine Learning'

DOI

10.17862/cranfield.rd.11558580.v1

Rights

CC BY 4.0

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