We propose a scheme to explicitly detect and resolve ambiguous situations in multiple target tracking. During periods of uncertainty, our method applies multiple local single target trackers to hypothesise short term tracks. These tracks are combined with the tracks obtained by a global multi-target tracker, if they result in a reduction in the global cost function. Since tracking failures typi...

The 3-D visual tracking of human limbs is fundamental to a wide array of computer vision applications including gesture recognition, interactive entertainment, biomechanical analysis, vehicle driver monitoring, and electronic surveillance. The problem of limb tracking is complicated by issues of occlusion, depth ambiguities, rotational ambiguities, and high levels of noise caused by loose fitti...

Tracking multiple road users is playing a significant role in autonomous vehicles and advanced driver assistance systems. Different from Multiple Target Tracking (MTT) in aerospace, the motion of the ground vehicles is likely constrained by their operational environment such as road and terrain. This information could be taken as additional domain knowledge and exploited in the development of t...

Many contend that driving an automobile involves multiple-object tracking. At this point, no one has tested this idea, and it is unclear how multiple-object tracking would coordinate with the other activities involved in driving. To address some of the initial and most basic questions about multiple-object tracking while driving, we modified the tracking task for use in a driving simulator, cre...

We present a computational model of multiple object tracking that makes trial-level predictions about the allocation of visual attention and the resulting performance. This model follows the intuition of allocated resources modulating spatial resolution, but it implements it in a specific way that leads to accurate predictions in multiple task manipulations. Experiments on human subjects, guide...

Using the multiple-object tracking paradigm, this study examines how spontaneous appraisal for facial beauty affects distributed attention to multiple faces in dynamic displays. Observers tracked attractive faces more effectively than unattractive faces in this task. Tracking performance was only affected by target attractiveness, suggesting an absence of appraisal for distractor attractiveness...

An interacting multiple model for multi-node target tracking algorithm was proposed based on a fuzzy neural network (FNN) to solve the multi-node target tracking problem of wireless sensor networks (WSNs). Measured error variance was adaptively adjusted during the multiple model interacting output stage using the difference between the theoretical and estimated values of the measured error cova...

In this paper we introduce a 'vehicle tracking' task, which tests the ability of a driver to track the location of multiple vehicles on the roadway. Based on the 'multiple object tracking' task (Pylyshyn & Storm, 1988), the vehicle tracking task presents the driver with an array of identical vehicles immediately in front of the subject vehicle. The task consists of three distinct stages: encodi...

Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distortions caused by RGB frames. To overcome these distortions, we propose a multiple-object fusion tracker (MOFT), which uses a combination of 3D point...

Tracking of video targets is the process of estimating the current and predicting the future state of a target from a sequence of video sensor measurements. Multitarget video tracking is complicated by the fact that targets can occlude one another and affect video feature measurements in a highly non-linear and difficult to model fashion., Tracking multiple targets that undergo repeated mutual ...