Ana Lopes, a student of Prof. Arnaldo Araújo and Prof. Jussara de Almeida, has compiled an impressive survey on human action recognition for her Ph.D. thesis. The analysis of that corpus, especially the recent literature, has prompted us to propose a new way to categorize the existing methods, using the underlying data representation as the main criterium of organization. The abstract explains the rationale behind that choice:
This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, realistic, “in the wild” videos. The proposed organization is based on the representation used as input for the recognition task, emphasizing the hypothesis assumed and thus, the constraints imposed on the type of video that each technique is able to address. Expliciting the hypothesis and constraints makes the framework particularly useful to select a method, given an application. Another advantage of the proposed organization is that it allows categorizing newest approaches seamlessly with traditional ones, while providing an insightful perspective of the evolution of the action recognition task up to now. That perspective is the basis for the discussion in the end of the paper, where we also present the main open issues in the area.
The survey was submitted for peer review at the CVIU, and is available as a preprint at arxiv.org.
