Watching the cities: big data and computer vision for analysis of urban environments

• Grant number: 15/03475-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2015
• End date: June 30, 2017
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Roberto Marcondes Cesar Junior
• Grantee: Gabriel Augusto Bianchi Azevedo Ferreira
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences, AP.TEM
• Associated scholarship(s): 16/12667-8 - Data-driven city model representation and analysis using visual and non-visual information, BE.EP.IC

Abstract

This work aims to develop and to apply methods for studying the urban environment through video. This study will be divided in two parts (or steps), related to the analysis of urban scenes. In the first part, we plan to constitute a database, which will gather information, in the form of videos and metadata, about urban environments. The first step includes designing the database, developing robots to capture data, along with using models and algorithms to assure the quality of the collected information. The second part will deal with data mining, which includes the interpretation of that huge amount of data obtained on the first step. The image analysis will focus on detecting three main elements: I) vehicles, II) buildings and III) pedestrians. For this purpose, we intend to use computer vision methods and algorithms, along with pattern recognition techniques. Most of the studies regarding urban environments and video cameras make use of these aforementioned basic elements. Therefore, there is a natural interest in detecting them.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

TOKUDA, ERIC K.; FERREIRA, GABRIEL B. A.; SILVA, CLAUDIO; CESAR-, ROBERTO M., JR.; IEEE. A NOVEL SEMI-SUPERVISED DETECTION APPROACH WITH WEAK ANNOTATION. 2018 IEEE SOUTHWEST SYMPOSIUM ON IMAGE ANALYSIS AND INTERPRETATION (SSIAI), v. N/A, p. 4-pg., 2018-01-01. (15/22308-2, 16/12077-6, 14/24918-0, 15/03475-5)