Influence of depth cues on multiple objects tracking in 3D scene

Two-dimensional and three-dimensional multiple object tracking learning performance in adolescent female soccer players: The role of flow experience reflected by heart rate variability

Three-dimensional multiple object tracking (3D-MOT) has been used in various fields to mimic real-life tracking, especially in perceptual-cognitive skills training for soccer. Yet, the learning efficiency in 3D-MOT tasks has not been compared with 2D-MOT. Further, whether the advantage can be reflected by heart rate variability (HRV) based on the neurovisceral integration model should also be examined. Therefore, we used both 2D- and 3D-MOT in a brief adaptive task procedure for adolescent female soccer players with HRV measurement. A faster tracking speed threshold of participants was found in the 3D- compared to 2D-MOT, as well as average tracking speed in the last training period of 3D-MOT. Moreover, lower low frequency (LF) components of HRV in the 3D-MOT indicated a flow experience, demonstrating the provision of more attentional resources. Therefore, we observed that adolescent female soccer players demonstrated higher learning efficiency in 3D-MOT tasks in virtual reality (VR) through a higher flow experience. This study examined the learning efficiency between the two MOT tasks in the soccer domain using evidence from HRV and highlighted the utility and applicability of 3D-MOT application.

Effect of depth information on multiple-object tracking in three dimensions: A probabilistic perspective

Many daily situations require us to track multiple objects and people. This ability has traditionally been investigated in observers tracking objects in a plane. This simplification of reality does not address how observers track objects when targets move in three dimensions. Here, we study how observers track multiple objects in 2D and 3D while manipulating the average speed of the objects and the average distance between them. We show that performance declines as speed increases and distance decreases and that overall tracking accuracy is always higher in 3D than in 2D. The effects of distance and dimensionality interact to produce a more than additive improvement in performance during tracking in 3D compared to 2D. We propose an ideal observer model that uses the object dynamics and noisy observations to track the objects. This model provides a good fit to the data and explains the key findings of our experiment as originating from improved inference of object identity by adding the depth dimension.

Many daily life situations require us to track objects that are in motion. In the laboratory, this multiple object tracking problem is classically studied with objects moving on a two-dimensional screen, but in the real world objects typically move in three dimensions. Here we show that, despite the complexity of seeing in depth, observers track multiple objects better when they move in 3D than 2D. A probabilistic inference model explains this by showing that the association of noisy visual signals to the objects that caused them is less ambiguous when depth cues are available. This highlights the role that depth cues play in our everyday ability to track objects.

Attentive tracking of moving objects in real 3D space

Results of earlier multiple object tracking (MOT) studies imply that humans can track several moving targets in a 2D environment simultaneously. Recently, a study suggested that stereoscopic depth has positive effect on tracking multiple objects when the objects are presented separately on multiple planes. However, it remains unclear whether or not humans can track moving targets in a real 3D environment. In this study, we investigated this issue displaying four targets and four distractors on near and/or far depth planes separated physically by 6, 10 or 50 cm using a half-mirror and two CRT-monitors. In addition we also tested whether participants could track the targets when either a target or a distractor changed depth during tracking. Our results suggested that performance dropped if the targets were presented on both depth planes especially when the distance between the planes was 50 cm. In addition, participants could track a depth-changed target if targets were presented on both planes before the start of a motion phase regardless of whether the initial state of targets distribution randomly varied or not, whereas they failed to track the target if all targets were presented on a single plane before MOT. In conclusion, humans have the ability to set attention on a wide range for MOT in a real 3D environment, with the provision that the efficiency of the tracking is critically dependent not only on the distance in depth but also on an initial state of distribution of the targets without the predictability of the initial state.