Detecting Deception in Movement: The Case of the Side-Step in Rugby

Although coordinated patterns of body movement can be used to communicate action intention, they can also be used to deceive. Often known as deceptive movements, these unpredictable patterns of body movement can give a competitive advantage to an attacker when trying to outwit a defender. In this particular study, we immersed novice and expert rugby players in an interactive virtual rugby environment to understand how the dynamics of deceptive body movement influence a defending player’s decisions about how and when to act. When asked to judge final running direction, expert players who were found to tune into prospective tau-based information specified in the dynamics of ‘honest’ movement signals (Centre of Mass), performed significantly better than novices who tuned into the dynamics of ‘deceptive’ movement signals (upper trunk yaw and out-foot placement) (p<.001). These findings were further corroborated in a second experiment where players were able to move as if to intercept or ‘tackle’ the virtual attacker. An analysis of action responses showed that experts waited significantly longer before initiating movement (p<.001). By waiting longer and picking up more information that would inform about future running direction these experts made significantly fewer errors (p<.05). In this paper we not only present a mathematical model that describes how deception in body-based movement is detected, but we also show how perceptual expertise is manifested in action expertise. We conclude that being able to tune into the ‘honest’ information specifying true running action intention gives a strong competitive advantage.

Vision Modulates Corticospinal Suppression in a Functionally Specific Manner during Movement of the Opposite Limb

The effect of vision on the excitability of corticospinal projections to the flexor carpi radialis (FCR) and extensor carpi radialis (ECR) muscles of right human forearm was investigated before and during discrete movement of the opposite limb. An external force opposed the initial phase of the movement (wrist flexion) and assisted the reverse phase, so that recruitment of the wrist extensors was minimized. Three conditions were used as follows: viewing the inactive right limb (Vision), viewing the mirror image of the moving left limb (Mirror), and with vision of the right limb occluded (No Vision). Transcranial magnetic stimulation was delivered to the left motor cortex: before, at the onset of, or during the left limb movement to obtain motor evoked potentials (MEPs) in the muscles of the right forearm. At and following movement onset, MEPs obtained in the right FCR were smaller in the Vision condition than in the Mirror and No Vision conditions. A distinct pattern of variation was obtained for the ECR. In all conditions, MEPs in this muscle were elevated upon or following movement of the opposite limb. An additional analysis of ipsilateral silent periods indicated that interhemispheric inhibition plays a role in mediating these effects. Activity-dependent changes in corticospinal output to a resting limb during discrete actions of the opposite limb are thus directly contingent upon where one looks. Furthermore, the extent to which vision exerts an influence upon projections to specific muscles varies in accordance with the functional contribution of their homologs to the intended action.

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.