Numerous studies have shown that important social information, such as gender, emotion, intention, and direction of motion, can be extracted from PLDs (Atkinson, Dittrich, Gemmell, & Young, 2004 Blakemore, 2008, 2012 Loula et al., 2005 Pollick, Kay, Heim, & Stringer, 2005 Pollick, Lestou, Ryu, & Cho, 2002 Rizzolatti et al., 2001 B.
KINECT RANDOM DOT PATTERN SKIN
Although highly impoverished-for instance, they do not provide information pertaining to skin color, hair, or clothing-once in motion, PLDs can rapidly be recognized as showing coherent and meaningful movements. Johansson ( 1973) successfully solved this issue by developing a point-light display (PLD) technique, which depicts human movements through a set of light points (e.g., 12 points) designated at distinct joints of the moving human body. Given that a considerable amount of non-BM-related information is contained in a scene (e.g., a person’s skin color, hair, and clothing), researchers have attempted to extract pure BM information by removing irrelevant data. To explore the mechanisms of BM, it is important to use a set of stimuli that can efficiently and elegantly convey the movements of animate entities. Thompson & Parasuraman, 2012 Urgen, Plank, Ishiguro, Poizner, & Saygin, 2013 van Kemenade, Muggleton, Walsh, & Saygin, 2012). Researchers from such varied areas as psychology, neuroscience, clinical sciences, and robotics, have investigated BM using behavioral, neuroimaging (ERP/EEG, fMRI, MEG, fNIRS, and TMS), and modeling methods (e.g., Bardi, Regolin, & Simion, 2011 Blakemore, 2008 Jaywant, Shiffrar, Roy, & Cronin-Golomb, 2016 Karg et al., 2013 Kawai, Asada, & Nagai, 2014 Kim, Doop, Blake, & Park, 2005 Koldewyn, Whitney, & Rivera, 2011 Loula, Prasad, Harber, & Shiffrar, 2005 Mather, Battaglini, & Campana, 2016 Miller & Saygin, 2013 Puce & Perrett, 2003 Rizzolatti, Fogassi, & Gallese, 2001 Shen, Gao, Ding, Zhou, & Huang, 2014 J. Unsurprisingly, research on BM has been among the most important and fruitful fields in visual/social cognition in the recent decade (for reviews, see Blake & Shiffrar, 2007 Pavlova, 2012 Puce & Perrett, 2003 Steel, Ellem, & Baxter, 2015 Troje, 2013). The processing capability of BM is currently suggested to be a hallmark of social cognition (Gao, Ye, Shen, & Perry, 2016 Pavlova, 2012). For instance, BM processing is critical for prosocial behavior and nonverbal communication (Blake & Shiffrar, 2007 Pavlova, 2012). It is one of the most important and sophisticated stimuli encountered in our daily lives. Therefore, we think that the KBC toolbox can be useful in generating BM for future research.īiological motion (BM) refers to the movement of animate entities (e.g., walking, jumping, or waving by humans Johansson, 1973 Troje, 2013). We conducted three experiments to examine whether KBC-generated BM can genuinely reflect the processing characteristics of BM: (1) Is BM from this source processed globally in vision? (2) Does its BM (e.g., from the feet) retain detailed local information? and (3) Does the BM convey emotional information? We obtained positive results in response to all three questions. The KBC toolbox aims to help researchers acquire PLD-based BM in an easy, low-cost, and user-friendly way.
KINECT RANDOM DOT PATTERN FREE
In this study, we propose a free Kinect-based biological motion capture (KBC) toolbox based on the Kinect Sensor 2.0 in C++. These factors impede the investigation of BM mechanisms.
Although these stimuli are highly precise, the motion capture system is expensive and bulky, and its process of constructing a PLD-based BM is time-consuming and complex. Most prevalent BM stimuli are created by state-of-the-art motion capture systems. To obtain pure BM, researchers nowadays predominantly use point-light displays (PLDs), which depict BM through a set of light points (e.g., 12 points) placed at distinct joints of a moving human body. Biological motion (BM) is the movement of animate entities, which conveys rich social information.
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