Abstract
AbstractActivity recognition is one of the most prolific fields of research. For this reason, there are new fields of research that expand the possibilities of the activity recognition: Group behavior recognition. This field does not limit the number of elements in the scene, and there are a lot of new elements that must be analyzed. Each group, like each individual element, has its behavior, but this behavior depends on their elements, and the relationships between these elements. All these new elements cause that group behavior recognition was a new field of research, with some similar elements but it must be studied apart. This way, group behavior recognition is a novel field, in which there are not many researches and there are not many datasets that could be used by researchers. This situation causes the slow advance of the science in this field. This paper tries to show a complete description of the problem domain, with all the possible variants, a formal description and show a novel architecture used to solve this issue. Also describes a specific group behavior recognition dataset, and shows how it could be used.KeywordsDatasetGroup behavior recognitionactivity representationcomputer vision
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