Viewing the Viewers: A Novel Challenge for Automated Crowd Analysis

Abstract

We focus on the automated analysis of spectator crowd, that is, people watching sport contests alive (in stadiums, amphitheaters etc.), or, more generally, people "watching the activities of an event [.. . ] interested in watching something specific that they came to see" [2]. This scenario differs substantially from the typical crowd analysis setting (e.g. pedestrians): here the dynamics of humans is more constrained, due to the architectural environments in which they are situated; people are expected to stay in a fixed location most of the time, limiting their activities to applaud, support/heckle the players or discuss with the neighbors. In this paper, we start facing this challenge by following a social signal processing approach, which grounds computer vision techniques in social theories. More specifically, leveraging on social theories describing expressive bodily conduct, we will show how, by using computer vision techniques, it is possible to distinguish fan groups belonging to different teams by automatically detecting their liveliness in different moments of the match, even when they are merged in the stands. Moreover, we will show how, only by automatically detecting crowd's motions on the stands, it is possible to single out the most salient events of the match, like goals, fouls or shots on goal.

Statistical Pattern Recognition Meets Formal Ontologies

“…The first methodological results obtained by following this new direction on object recognition can be found in [12,13,2] and on video understanding in [4,3]. Together with papers, practical industrial applications tested as prototypes during the Winter Universiade in Trento 1 are going to be finalized, showing that the potentialities of this new perspective [11] are not limited to a mere theoretical dimension [5].…”

“…Such symbolic stances have been long studied in the sociological literature and can be deployed to give much more fine-grained scene automatic interpretations. Our first studies have been focused on getting video data, and to study ontologies to describe the activities going on in a stadium [4,3,5]. An ontology, if appropriately instructed by the outcomes of sociological studies, should be able to infer meaningful symbolic behavior of individuals or groups in the crowd, given the composition of elementary movements performed by spectators, like sitting with crossed legs, standing up, clapping hands etc.…”

From the lab to the world

“…Studies like the ones carried out in [6] and [11] present relevant insights on these matters. They demonstrate that fans prefer to be among a high-density crowd, even if that means being in a smaller venue, and show that factors like the spectators' excitement level can be inferred by observing the crowd activity.…”

Bringing the sport stadium atmosphere to remote fans

“…Moreover, the analysis of the crowd during live sports is of great importance to understand single and social behaviors between fans, and how they react to different events. Studies like the ones carried out in [11] and [12] present relevant insights on these matters, showing that fans prefer to be among a high density crowd, even if it means being in a Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored.…”