English
This project aims to explore new research problems that can be solved by using image and video data analysis. This project will be developed in collaboration with the Lisbon City Council (CML) and addresses challenges that CML launched for the scientific community. The area topic to be addressed is computer vision for knowledge extraction based on aerial and street-level city imagery. We propose a new multi-spatial scale urban fabric dataset and a novel convolutional neural network solution for urban fabric classification tasks. Considering the challenges launched by CML and the already established collaboration between Iscte and CML, this project proposes to explore solutions to a set of urban classification problems by using video and image analysis. In this topic the goal is to identify features of the city shape, namely: i) to estimate the existence of unregistered greenspaces, as green rooftops (since CML is not currently aware of most green rooftops existing in Lisbon) and green back yards (not registered in the city council); ii) to estimate the height and deployment shape and area of Lisbon’s buildings, which will enable to develop an automatic and constantly updated tri-dimensional urban fabric map for Lisbon; iii) to estimate and automatically classify the conservation state of buildings’ facades; iv) among others. Such a methodology will be initially based on the set of aerial and street-level images obtained from CML (during the period of the scholarship). We are also considering exploiting existing city plans freely available at OpenStreetMaps to boost the convolutional neural network's training process, as well as to improve its inference performance. In a second phase, we will explore the use of other types of images such as from google street viewer and the ones directly collected by cameras in drones or city council vehicles (e.g., garbage trucks). For this second phase, we envision submitting a proposal to competitive funding and propose this topic as a master dissertation. The proposed project is multidisciplinary, inter-group (SSE and DLS), and aligns with ISTAR core lines of Smart Cities and Digital Transformation.
| Centro de Investigação | Grupo de Investigação | Papel no Projeto | Data de Início | Data de Fim |
|---|---|---|---|---|
| ISTAR-IUL | Software Systems Engineering | Parceiro | 2021-09-01 | 2022-02-28 |
Não foram encontrados registos.
| Nome | Afiliação | Papel no Projeto | Data de Início | Data de Fim |
|---|---|---|---|---|
| Joao C Ferreira or Joao Ferreira | Professor Auxiliar (com Agregação) (DCTI); Investigador Integrado (ISTAR-IUL); | Coordenador Global | 2021-09-01 | 2022-02-28 |
| Sara Eloy | Professora Auxiliar (DAU); Investigadora Integrada (ISTAR-IUL); | Investigadora | 2021-09-01 | 2022-02-28 |
| Tiago Fonseca | -- | Investigador | 2021-09-01 | 2022-02-28 |
| Tomás Gomes Silva Serpa Brandão | Professor Auxiliar (DCTI); Investigador Integrado (ISTAR-IUL); | Investigador | 2021-09-01 | 2022-02-28 |
| Código/Referência | DOI do Financiamento | Tipo de Financiamento | Programa de Financiamento | Valor Financiado (Global) | Valor Financiado (Local) | Data de Início | Data de Fim |
|---|---|---|---|---|---|---|---|
| UIDP/04466/2020 | -- | Contrato | FCT - Financiamento Plurianual de Unidades de ID - Portugal | 5900 | 5900 | 2021-09-01 | 2022-02-28 |
Não foram encontrados registos.
Não foram encontrados registos.
Não foram encontrados registos.
Não foram encontrados registos.
Com o objetivo de aumentar a investigação direcionada para o cumprimento dos Objetivos do Desenvolvimento Sustentável para 2030 das Nações Unidas, é disponibilizada no Ciência-IUL a possibilidade de associação, quando aplicável, dos projetos científicos aos Objetivos do Desenvolvimento Sustentável. Estes são os Objetivos do Desenvolvimento Sustentável identificados para este projeto. Para uma informação detalhada dos Objetivos do Desenvolvimento Sustentável, clique aqui.
