polito.it
Politecnico di Torino (logo)

Efficient and scalable visual place recognition

Emanuele Munafo'

Efficient and scalable visual place recognition.

Rel. Barbara Caputo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (22MB) | Preview
Abstract:

Visual Place Recognition (VPR) is the task of recognizing what place is represented in a given image. This task, which is being studied for decades, is rich of challenges and margins for improvements. The main purpose of this thesis was to study techniques to improve the scalability of VPR algorithms without penalizing their precision. This work contains many experiments that show which improvement can be achieved by applying similar architectures and what their limitations are. Moreover, a software made up by APIs back-end calls and a user-friendly front-end, was developed to potentially allow every user to perform searches on large scale in just a matter of seconds. The software offers also features like user roles, authentication, high performance and flexibility by design. The Flask API allows a more scalable deployment.

Relatori: Barbara Caputo
Anno accademico: 2020/21
Tipo di pubblicazione: Elettronica
Numero di pagine: 97
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-32 - INGEGNERIA INFORMATICA
Aziende collaboratrici: Fondazione IIT
URI: http://webthesis.biblio.polito.it/id/eprint/18095
Modifica (riservato agli operatori) Modifica (riservato agli operatori)