Pattern recognition in Latin America in the "big data" era

The "Big Data" era has arisen, driven by the increasing availability of data from multiple sources such as social media, online transactions, network sensors or mobile devices. This is currently a focus of interest among public and private organizations, governments, research institutes and companies operating in diverse fields as health, security, commercial recommendations, detection of anomalies and future trends among others. In this problem, the main objective is to recognize and extract meaningful information (patterns, structure, underlying relationships, etc.) from huge amounts of heterogeneous data. This task is complicated by new, significant storage and processing requirements due to unprecedented volumes of data. In this scenario, new algorithms in Pattern Recognition and related fields are being devised, while well known techniques are revisited and adapted to these new challenges. Latin American research in the "Big Data" problem is still incipient, but there is a significant body of recent works in the subjects of Pattern Recognition and related fields that indirectly addresses the problem. This paper reviews Latin American contributions in Pattern Recognition and related fields in the last lustrum. The focus is set on-but not restricted to-applications in the fields of Computer Vision and Image Analysis with large scale characteristics.