CrowdPet: applying computer vision in the identification of lost pets
Abstract
Brazil, as well as several other developing countries, has a significant problem regarding street animal populations. Aside the cruel conditions, this situation represents risks for public health, since animals may become sick and procreate at alarming rates. We intend to employ technological solutions -- specifically, computer vision and machine learning methods -- in order to approach this urban problem in a collaborative fashion, making it easier for citizens to take part in the process of identification and collecting relevant data on these animals. This project is defined in the context of the CrowdPet service, which will be made available to users through a smartphone application and will improve various aspects related to the problem, such as acquisition and intelligent processing of real data on animal populations, automatic localization of lost animals, and accountability in the guardianship of dogs and cats. We present partial results obtained during PIPE Phase 1, which include crucial strategic partnerships with governmental, private, and non-governamental (NGO) organizations, showing the evolution of the original concept into a thorough, applicable and commercially viable solution. Partial technical results of the scholarship holders and third parties are also discussed in general terms. (AU)
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