Automatically detecting groups of conversing people has become a hot challenge, although a formal, widely-accepted definition of them is lacking. This gap can be filled by considering the social psychological notion of an F-formation as a loose geometric arrangement. In the literature, two main approaches followed this line, exploiting Hough voting [1] from one side and Graph Theory [2] on the other. This paper offers a thorough comparison of these two methods, highlighting the strengths and weaknesses of both in different real life scenarios. Our experiments demonstrate a deeper understanding of the problem by identifying the circumstances in which to adopt a particular method. Finally our study outlines what aspects of the problem are important to address for future improvements to this task.
GROUP DETECTION IN STILL IMAGES BY F-FORMATION MODELING: A COMPARATIVE STUDY
Setti Francesco;
2013
Abstract
Automatically detecting groups of conversing people has become a hot challenge, although a formal, widely-accepted definition of them is lacking. This gap can be filled by considering the social psychological notion of an F-formation as a loose geometric arrangement. In the literature, two main approaches followed this line, exploiting Hough voting [1] from one side and Graph Theory [2] on the other. This paper offers a thorough comparison of these two methods, highlighting the strengths and weaknesses of both in different real life scenarios. Our experiments demonstrate a deeper understanding of the problem by identifying the circumstances in which to adopt a particular method. Finally our study outlines what aspects of the problem are important to address for future improvements to this task.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
