Multiple people tracking is a key problem for many applications such as surveillance, animation or car navigation, and a key input for tasks such as activity recognition. In crowded environments occlusions and false detections are common, and although there have been substantial advances in recent years, tracking is still a challenging task. Tracking is typically divided into two steps: detecti...

How are attentional priorities set when multiple stimuli compete for access to the limited-capacity visual attention system? According to Pylyshyn (1989) and Yantis and Johnson (1990), a small number of visual objects can be preattentively indexed or tagged and thereby accessed more rapidly by a subsequent attentional process (e.g., the traditional "spotlight of attention"). In the present stud...

This paper presents an algorithm for multiple-object tracking without using object detection. We concentrate on creating long-term trajectories for unknown moving objects by using a model-free tracking algorithm. Each individual object is tracked by modeling the temporal relationship between sequentially occurring local motion patterns. The algorithm is based on shape and motion descriptors of ...

Which coordinate system do we use to track moving objects? In a previous study using smooth pursuit eye movements, we argued that targets are tracked in both retinal (retinotopic) and scene-centered (allocentric) coordinates (Howe, Pinto, & Horowitz, 2010). However, multiple object tracking typically also elicits saccadic eye movements, which may change how object locations are represented. Obs...

Difficulties in visual attention are often implicated in autism spectrum disorders (ASD) but it remains unclear which aspects of attention are affected. Here, we used a multiple object tracking (MOT) task to quantitatively characterize dynamic attentional function in children with ASD aged 5-12. While the ASD group performed significantly worse overall, the group difference did not increase wit...

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...

In this paper we show how a combination of multiple neuromorphic vision sensors can achieve the same higher level visual processing tasks as carried out by a conventional vision system. We process the multiple neuromorphic sensory signals with a standard auto-regression method in order to fuse the sensory signals and to achieve higher level vision processing tasks at a very high update rate. We...

This paper presents a technique for object tracking by using CAMSHIFT algorithm that tracks an object based on color. We aim to improve the CAMSHIFT algorithm by adding a multiple targets tracking function [1].When one object is selected as a template, it will search objects that have the same hue value and shape by shape recognition. Hence, the inputs of the algorithm are hue values and shape ...

People can keep track of target objects as they move among identical distractors using only spatiotemporal information. We investigated whether or not participants use motion information during the moment-to-moment tracking of objects by adding motion to the texture of moving objects. The texture either remained static or moved relative to the object's direction of motion, either in the same di...

Contrary to other tasks (free viewing, recognition, visual search), participants often fail to recognize repetition of trials in multiple object tracking (MOT). This study examines the intra- and interindividual variability of eye movements in repeated MOT trials along with the adherence of eye movements to the previously described strategies. I collected eye movement data from 20 subjects duri...