Laughter Type Recognition from Whole Body Motion

Human Perception of Laughter from Context-Free Whole Body Motion Dynamic Stimuli

“…Again we make no claims in this paper to know what the specific movements are that the participants are using to rate intensity; however, [15] provides insights concerning the specific movements that can be used to categorise laughter type, using a different set of raters; these movements may be candidates for informing the perception of laughter intensity.…”

“…Some suggestions have been made concerning the appropriate muscular movements associated with laughter. Mancini et al [14] propose a Body Laughter Index (BLI), and [15] focussed on a range of key movements associated with laughter perception. In this study we do not address directly what features of the movement are important for rating the intensity of a laugh ( [15] addresses features that may be involved in laughter categorisation), we assume that most humans will have a degree of expertise regarding the ability to define a laugh as intense or not.…”

“…Mancini et al [14] propose a Body Laughter Index (BLI), and [15] focussed on a range of key movements associated with laughter perception. In this study we do not address directly what features of the movement are important for rating the intensity of a laugh ( [15] addresses features that may be involved in laughter categorisation), we assume that most humans will have a degree of expertise regarding the ability to define a laugh as intense or not. Therefore in this study we leave the interpretation of intensity of laughter up to the human "expert" and do not provide any explicit instructions regarding movements that they would expect to produce an intense laugh.…”

“…This differs from [15] which uses modal laughter perceptions to investigate the automatic recognition of laughter type based on features of body movement. A total of 6802 laugh judgements of the 126 laughs produced a mean participant categorisation level of 28.85 laughs correctly categorised, with a standard deviation of 6.1.…”

Laughter Research: A Review of the ILHAIRE Project

“…Two data gathering sessions were dedicated to collecting this data. One in Belfast developed the laughter induction techniques (McKeown et al [72]), and was followed by a similar session conducted at UCL in which the motion capture data was made available as part of the database (Griffin et al [40]; McKeown et al [71]). The available data consists of 126 animated "stick figure" video stimuli of laughter that has been categorized as either hilarious, social, fake, awkward or not a laugh.…”