Virtual Thrower Versus Real Goalkeeper
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Nicolas Vignais* Virtual Thrower Versus Real M2S Laboratory, UFR APS, Rennes 2-ENS Cachan University, Goalkeeper: The Influence 35044 Rennes, France of Different Visual Conditions Richard Kulpa on Performance M2S Laboratory, UFR APS, Rennes 2-ENS Cachan University, 35044 Rennes, France and IRISA BUNRAKU Project, Abstract Campus de Beaulieu, 35042 Rennes, France In order to use virtual reality as a sport analysis tool, we need to be sure that an immersed athlete reacts realistically in a virtual environment. This has been validated Cathy Craig for a real handball goalkeeper facing a virtual thrower. However, we currently ignore School of Psychology, Queen’s which visual variables induce a realistic motor behavior of the immersed handball goal- University Belfast, Northern Ireland keeper. In this study, we used virtual reality to dissociate the visual information related to the movements of the player from the visual information related to the trajectory of Benoit Bideau the ball. Thus, the aim is to evaluate the relative influence of these different visual infor- M2S Laboratory, UFR APS, mation sources on the goalkeeper’s motor behavior. We tested 10 handball goalkeep- Rennes 2-ENS Cachan University, ers who had to predict the final position of the virtual ball in the goal when facing the 35044 Rennes, France following: only the throwing action of the attacking player (TA condition), only the resulting ball trajectory (BA condition), and both the throwing action of the attacking player and the resulting ball trajectory (TB condition). Here we show that performance was better in the BA and TB conditions, but contrary to expectations, performance was substantially worse in the TA condition. A significant effect of ball landing zone does, however, suggest that the relative importance between visual information from the player and the ball depends on the targeted zone in the goal. In some cases, body- based cues embedded in the throwing actions may have a minor influence on the ball trajectory and vice versa. Kinematics analysis was then combined with these results to determine why such differences occur depending on the ball landing zone and conse- quently how it can clarify the role of different sources of visual information on the motor behavior of an athlete immersed in a virtual environment. 1 Introduction Virtual reality is now being used as a tool to analyze and understand motor behavior in sport (Katz et al., 2006; Bideau et al., 2010). This promising technology has a number of advantages over video presentation or real-game situations. Firstly, all factors can be controlled and manipulated in a systematic manner, ensuring reproducibility between trials (Tarr & Warren, 2002). Sec- ondly, the effects of these modifications on the resulting behavior can be moni- tored in real time. Thirdly, the immersion of the subject in the virtual scene in an egocentric position allows the optical information gleaned from the virtual world to correspond directly to what the participant would see in a real sporting Presence, Vol. 19, No. 4, August 2010, 281–290 ª 2010 by the Massachusetts Institute of Technology *Correspondence to [email protected]. Vignais et al. 281 Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/PRES_a_00003 by guest on 27 September 2021 282 PRESENCE: VOLUME 19, NUMBER 4 situation (Cutting, 1997). Finally, the participant’s view- nent’s next move (Abernethy, Wood, & Parks, 1999). point is stereoscopic which has previously been high- While some studies have suggested that successful antici- lighted as an important factor when performing inter- pation is determined by the perception of spatial-tempo- ceptive tasks (Mazyn, Lenoir, Montagne, & Savelsbergh, ral information in the trajectory of the ball (Bastin, Craig, 2004). Given these advantages, this technology has been & Montagne, 2006; Craig et al., 2006; Lenoir, Musch, exploited to analyze and understand players’ perform- Thiery, & Savelsbergh, 2002; McLeod, Reed, & Dienes, ance in different sports such as soccer (Craig, Berton, 2006), others have shown that successful anticipatory Rao, Fernandez, & Bootsma, 2006), tennis (Molet behavior depends on the accurate perception of body- et al., 1999), handball (Bideau et al., 2004; Vignais based cues (Jackson, Warren, & Abernethy, 2006; Pan- et al., 2009), and rugby (Brault, Bideau, Kulpa, & Craig, chuk & Vickers, 2006; Savelsbergh, Williams, Van der 2009). Moreover this technology can be employed to Kamp, & Ward, 2002; Williams, Davids, Burwitz, & Wil- test team sport strategies (Metoyer & Hodgins, 2000) liams, 1994). The general consensus suggests that when or to train athletes in a simulator (Kelly & Hubbard, the temporal constraints are too tight (e.g., a penalty kick 2000). With respect to this latter option, Kelly and Hub- in soccer), players do not have enough time to act on ball bard have successfully designed a complete bobsled sim- trajectory information and consequently use body-based ulator which displays a graphical representation from the cues (Savelsbergh, Van der Kamp, Williams, & Ward, driver’s viewpoint on a cockpit-mounted monitor. 2005). In spite of this conclusion, the relative contribu- In spite of these advantages, using virtual reality as a tion of body-based versus ball flight information in per- sports analysis tool does raise new questions. One of the formance has not been properly tested. most important is the motor response of the athlete Here, we present body-based cues and ball trajectory immersed in a virtual environment. In fact, the motor information in isolation in order to better assess the rela- behavior of a subject can be considered as one of the tive importance of both types of visual information for physical measures of presence (Slater, 2009; Slater, performance. Using immersive interactive virtual reality, Khanna, Mortensen, & Yu, 2009). In sport, this concept this study allows dissociation between body-based cues has been used to validate a virtual sport situation. and ball flight information. The relative importance of Indeed, Bideau et al. (2003) compared the movement of these two visual elements in performance will be assessed handball goalkeepers during the interception of the same in order to understand why an athlete tends to respond throws made by real and virtual opponents. The results realistically to a virtual sport situation. To this end, we showed that the goalkeepers’ gestures in both environ- investigate the effects of different visual conditions of a ments were similar. Although we know that the virtual virtual throwing action on the performance of immersed sport situation used in this case study induced handball handball goalkeepers. goalkeepers to respond realistically, we do not yet know why they did. Are some visual elements displayed in the 2 Overview virtual scene more important than others to enable handball goalkeepers to react in a realistic way? In order to evaluate the influence of the different In most ball sports, successful anticipation of what an visual conditions of a throwing action on the handball opponent is going to do next can give a substantial com- goalkeepers’ performance, we developed a three-step petitive edge. The temporal constraints within which a process (see Figure 1). player must act are often very tight, and so early recogni- Step 1. First of all, to realistically animate the tion of an opponent’s actions or anticipation of where synthetic thrower and the ball in the virtual the ball is going can increase the player’s chances of environment, we captured real throwing making a successful counteracting move. Much of the actions. This led to the creation of a large research to date has focused on identifying the sources of motion database with throws to various visual information that players use to anticipate an oppo- places in the goal. Downloaded from http://www.mitpressjournals.org/doi/pdf/10.1162/PRES_a_00003 by guest on 27 September 2021 Vignais et al. 283 Figure 1. The three-step process includes data acquisition, real time experiment, and performance comparison. Step 2. Secondly, these captured throws were used segment, with six markers being reserved for the ball. by the MKM animation engine (Kulpa, Each player was asked to throw the ball 12 m from the Multon, & Arnaldi, 2005; Multon, Kulpa, goal, aiming for different prespecified target zones & Bideau, 2008) in order to realistically within the goal (no goalkeeper was present). For each animate the virtual character. The rendering of throw, the participant and ball movement were captured these animations was done with three different at 200 Hz using 12 infrared cameras. Nine trajectories visual conditions. that arrived close to the center of each zone were Step 3. Finally, the movements of the goalkeepers selected and used in the subsequent virtual animation were captured in real time. These data were part of the study (see Figure 2). then analyzed to determine which responses Kinematic throwing data, captured using the Vicon were successful. system, were then incorporated into the MKM (Manage- able Kinematic Motion) animation engine (Kulpa et al., 3 Motion Capture and Animation Process 2005; Multon et al., 2008) to animate the virtual hand- ball player in real time. Based on these captured motions, In order to animate the virtual character and the MKM can automatically synchronize, blend, and adapt ball, real handball throwing actions were recorded. actions to different morphologies and to external con- A Vicon motion capture system (Oxford Metrics, straints such as foot contacts. Virtual ball trajectories for Oxford, UK) was used to record movement kinematics the nine zones were calculated using another software from three top-level handball players. All the throwers module that incorporates data obtained from the motion were right-handed and had at least 10 years experience capture part of the study. Ball velocities were similar for playing handball in the top French league at the time of all nine trajectories (20 6 0.2 mÁsÀ1), making ball flight the study. Each player was equipped with 36 reflective time very nearly the same for all nine zones.