Tracking Multiple Objects Is Limited Only by Object Spacing, Not by Speed, Time, or Capacity

2010 ◽  
Vol 21 (7) ◽  
pp. 920-925 ◽  
Author(s):  
S.L. Franconeri ◽  
S.V. Jonathan ◽  
J.M. Scimeca
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Multiple Object Tracking ◽  
Single Object ◽  
Multiple Objects ◽  
Performance Constraints ◽  
Root Cause ◽  
Multiple Object ◽  
Tracking Time ◽  
Environment Performance

In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors—the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the root cause of all performance constraints in multiple-object tracking. In two experiments, we found that as long as the distribution of object spacing is held constant, tracking performance is unaffected by large changes in object speed and tracking time. These results suggest that barring object-spacing constraints, people could reliably track an unlimited number of objects as fast as they could track a single object.

Re-Identification with Pre-Filtering by Image Quality for Multiple Objects Tracking

2021 ◽  
Vol 27 (8) ◽  
pp. 409-418
Author(s):  
A. D. Grigorev ◽  
◽  
A. N. Gneushev ◽  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Object Tracking ◽  
Multiple Object Tracking ◽  
Tracking Problem ◽  
Multiple Objects ◽  
Multiple Object ◽  
Objects Tracking ◽  
Error Accumulation ◽  
The Stability

The paper considers multiple object tracking. Existing methods tend to be either resource-intensive or prone to high object densities errors failing to provide competitive performance at high frame rates without significant tracking disruptions and error accumulation. We formulate the multiple object tracking problem under the assumption of linearity and independence of the movement of objects. The factorization of the posterior distribution of objects' parameters provides proof of the equivalence of the initial problem and the tracking procedure containing two subtasks: track prediction and assignment of measurements and objects. A modification of the assignment cost is introduced to achieve the stability of assignments in challenging scenarios of tracking, such as multiple objects occlusions and missing detections. We consider adding a term that states to re-identification of the candidate by comparing its descriptor with descriptors from the track history. Given that track measurements are not equal in terms of usefulness for re-identification, we introduce the technique of track descriptor pre-filtering based on quality assessment in order to select the most relevant descriptors for re-identification and reduce method algorithmic complexity. Both known quality assessment methods and an alternative detector-based approach are taken into account. Computational experiments were conducted on MOT20-01, MOT20-02 datasets containing CCTVcameras data in order to compare the proposed method with other approaches. The results showed the computational efficiency of the proposed methods and the increased stability of tracking in complex scenarios.

scholarly journals Noisy Perceptual Expectations: Multiple Object Tracking Benefits When Objects Obey Features of Realistic Physics

2018 ◽  
Author(s):  
Jonas Sin-Heng Lau ◽  
Timothy F. Brady
Keyword(s):  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Objects ◽  
Trajectory Estimation ◽  
Newtonian Physics ◽  
Low Level ◽  
Multiple Object

When objects move, their motion is governed by the laws of physics. We investigated whether multiple objects that move while correctly obeying aspects of Newtonian physics are easier to track than those that do not accurately obey the laws of physics. Participants were asked to track multiple objects that either did or did not take on the correct angles and/or speeds after collisions with each other. We found an advantage for tracking when objects obeyed realistic physics, such that people were more accurate when objects reflected from each other at proper angles and when objects varied in speed after collisions (as opposed to always maintaining the same speed). This advantage was independent of a variety of low-level factors that would be expected to affect object tracking, such as object spacing. However, we also found that performance was not affected when objects' speed changed randomly after each collision (so long as it varied), nor when the reflection angles were jittered moderately after collisions. We conclude that perceptual noise seriously limits many aspects of object trajectory estimation, but nevertheless people are sensitive to at least a subset of the Newtonian laws of physics under demanding attentional tracking conditions.

scholarly journals Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification

2019 ◽  
Vol 9 (22) ◽  
pp. 4771 ◽  
Author(s):  
Muyu Li ◽  
Xin He ◽  
Zhonghui Wei ◽  
Jun Wang ◽  
Zhiya Mu ◽  
...  
Keyword(s):  
Object Tracking ◽  
Multiple Object Tracking ◽  
Single Object ◽  
Complex Scene ◽  
Whole Process ◽  
Multiple Object ◽  
Binary Channel ◽  
Complex Scenes ◽  
Verification Model ◽  
Tracking Objects

Tracking objects over time, i.e., identity (ID) consistency, is important when dealing with multiple object tracking (MOT). Especially in complex scenes with occlusion and interaction of objects this is challenging. Significant improvements in single object tracking (SOT) methods have inspired the introduction of SOT to MOT to improve the robustness, that is, maintaining object identities as long as possible, as well as helping alleviate the limitations from imperfect detections. SOT methods are constantly generalized to capture appearance changes of the object, and designed to efficiently distinguish the object from the background. Hence, simply extending SOT to a MOT scenario, which consists of a complex scene with spatially mixed, occluded, and similar objects, will encounter problems in computational efficiency and drifted results. To address this issue, we propose a binary-channel verification model that deeply excavates the potential of SOT in refining the representation while maintaining the identities of the object. In particular, we construct an integrated model that jointly processes the previous information of existing objects and new incoming detections, by using a unified correlation filter through the whole process to maintain consistency. A delay processing strategy consisting of the three parts—attaching, re-initialization, and re-claiming—is proposed to tackle drifted results caused by occlusion. Avoiding the fuzzy appearance features of complex scenes in MOT, this strategy can improve the ability to distinguish specific objects from each other without contaminating the fragile training space of a single object tracker, which is the main cause of the drift results. We demonstrate the effectiveness of our proposed approach on the MOT17 challenge benchmarks. Our approach shows better overall ID consistency performance in comparison with previous works.

An New Method for Multi-Object Tracking Using Energy Minimization-Based Data Association

2013 ◽  
Vol 427-429 ◽  
pp. 1822-1825
Author(s):  
Zhen Hai Wang ◽  
Ki Cheon Hong
Keyword(s):  
Object Tracking ◽  
Energy Minimization ◽  
Moving Objects ◽  
Data Association ◽  
Multiple Object Tracking ◽  
Object Extraction ◽  
Frame Difference ◽  
Multiple Object ◽  
Important Research Topic ◽  
Key Steps

multiple object tracking is an active and important research topic. It faces many challenging problems. Object extraction and data association are two most key steps in multiple object tracking. To improve tracking performance, this paper proposed a tracking method which combines Kalman filter and energy minimization-based data association. Moving objects are segmented through frame difference. Its can be consider as the vertex. All detections in adjacent frames are be used to construct a graph. The energy is finally minimized with a graph cuts optimization. Data association can be consider as multiple labeling problems. Object corresponding can be obtained through energy minimization. Experiment results demonstrate this method can be accurately tracking two moving objects.

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

Psihologija ◽  
2010 ◽  
Vol 43 (4) ◽  
pp. 389-409 ◽  
Author(s):  
Vesna Vidakovic ◽  
Suncica Zdravkovic
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Relative Size ◽  
Multiple Object Tracking ◽  
Texture Gradient ◽  
Depth Cues ◽  
3D Space ◽  
Tracking Tasks ◽  
Multiple Object ◽  
3D Scene

Multiple-object-tracking tasks require an observer to track a group of identical objects moving in 2D space. The current study was conducted in an attempt to examine object tracking in 3D space. We were interested in testing influence of classical depth cues (texture gradients, relative size and contrast) on tracking. In Experiment 1 we varied the presence of these depth cues while subjects were tracking four (out of eight) identical, moving objects. Texture gradient, a cue related to scene layout, did not influence object tracking. Experiment 2 was designed to clarify the differences between contrast and relative size effects. Results revealed that contrast was a more effective cue for multiple object tracking in 3D scenes. The effect of occlusion was also examined. Several occluders, presented in the scene, were occasionally masking the targets. Tracking was more successful when occluders were arranged in different depth planes, mimicking more natural conditions. Increasing the number of occlusions led to poorer performance.

scholarly journals Color influences identification of the moving objects more than shape

Psihologija ◽  
2009 ◽  
Vol 42 (1) ◽  
pp. 79-93 ◽  
Author(s):  
Vesna Vidakovic ◽  
Suncica Zdravkovic
Keyword(s):  
Object Tracking ◽  
Cognitive Processes ◽  
Moving Objects ◽  
Multiple Object Tracking ◽  
Cognitive System ◽  
Attentional Processes ◽  
Spatiotemporal Characteristics ◽  
Multiple Object ◽  
Different Characteristics ◽  
As If

When people track moving objects, they concentrate on different characteristics. Recent results show that people more often concentrate on spatiotemporal than featural properties of the objects. In other words, location and direction of motion seem to be more informative properties than the stable featural characteristics. This finding contradicts some of our knowledge about cognitive system. Current research was done in attempt to specify the effect of featural characteristics, especially color and shape. In Experiment 1, subjects were asked to track four mobile targets presented with another four moving objects. After the motion has stopped, they had to mark the initial four targets. Our results have shown that participants pay more attention to the featural properties than to spatiotemporal characteristics. Since our task was more difficult than the tasks typically reported in the literature, the results might be interpreted as if the subjects relied mostly on attentional processes. The task in Experiment 2 was made even more difficult: the subjects were asked to direct attention on identity of every target. Consequently, the task demanded more complex cognitive processes and emphasizing effects of featural properties. Results suggest that color and shape does not have the same influences on multiple object tracking, but that color has more significant effect.

Distractor Locations Influence Multiple Object Tracking Beyond Interobject Spacing

2015 ◽  
Vol 62 (3) ◽  
pp. 170-180 ◽  
Author(s):  
Hauke S. Meyerhoff ◽  
Frank Papenmeier ◽  
Georg Jahn ◽  
Markus Huff
Keyword(s):  
Object Tracking ◽  
Target Tracking ◽  
Moving Objects ◽  
Multiple Object Tracking ◽  
Tracking Performance ◽  
Displacement Effect ◽  
Inhibitory Processes ◽  
Multiple Object ◽  
Displacement Angle

Human observers are able to keep track of several independently moving objects among other objects. Within theories of multiple object tracking (MOT), distractors are assumed to influence tracking performance only by their distance toward the next target. In order to test this assumption, we designed a variant of the MOT paradigm that involved spatially arranged target-distractor pairs and sudden displacements of distractors during a brief flash. Critically, these displacements maintained target-distractor spacing. Our results show that displacing distractors hurts tracking performance (Experiment 1). Importantly, target-distractor confusions occur within target-distractor pairs with displaced distractors (Experiment 2). This displacement effect increases with an increasing displacement angle (Experiment 3) but is equal at different distances between target and distractor (Experiment 4). This finding illustrates that distractors influence tracking performance beyond pure interobject spacing. We discuss how inhibitory processes as well as relations between targets and distractors might interfere with target tracking.

Improving Multiple Object Tracking with Single Object Tracking

2021 ◽  
Author(s):  
Linyu Zheng ◽  
Ming Tang ◽  
Yingying Chen ◽  
Guibo Zhu ◽  
Jinqiao Wang ◽  
...  
Keyword(s):  
Object Tracking ◽  
Multiple Object Tracking ◽  
Single Object ◽  
Multiple Object

scholarly journals 0254 The Effects of Chronic Sleep Restriction on Multiple Object Tracking

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A97-A97
Author(s):  
G Costedoat ◽  
C S Feria ◽  
S Pradhan ◽  
L S Stone ◽  
E E Flynn-Evans
Keyword(s):  
Object Tracking ◽  
Moving Objects ◽  
Multiple Object Tracking ◽  
Sleep Restriction ◽  
Naval Research ◽  
Attentional Processing ◽  
Air Traffic Controllers ◽  
Multiple Object ◽  
Office Of Naval Research ◽  
Chronic Sleep

Abstract Introduction The ability to simultaneously track numerous moving objects in the presence of irrelevant stimuli is essential for successfully carrying out a variety of tasks. Sleep loss impairs neurocognitive functioning and, as a result, attentional processing capacity is reduced. The objective of the current study was to determine if performance on the multiple object tracking (MOT) task was adversely impacted by a week of chronic sleep restriction (CSR). Methods Twelve healthy participants (6 males, 6 females) kept a fixed sleep-wake schedule, with a constant waketime, at home for four weeks (actigraphy confirmed compliance). During weeks one and three, participants maintained 9 hours in bed. During weeks two and four, participants were randomly assigned to 5 and 9 hours of sleep. Following weeks two and four, participants completed a 13-hour laboratory visit under dim light (< 15 lux), where they maintained a constant posture and were provided with hourly isocaloric snacks. MOT was presented at approximately 6 and 8 hours after waking. Participants were required to track four, five, or six moving targets in the presence of identical distractors (always 12 total objects). Results Participants slept significantly less when assigned to 5 (M = 4.43 hours, SD = 0.33 hours), compared to 9 hours of sleep (M = 7.42 hours, SD = 0.42 hours; F (1, 22) = 206.89, p = 0.00). The proportion of correct MOT responses was significantly lower following 5 (M = 0.70, SD = 0.15) compared to 9 hours of sleep (M = 0.77, SD = 0.12; F (1, 22) = 10.29, p < .05). Conclusion A week of CSR adversely impacted MOT performance compared to a week of sleep satiation. These findings have implications for individuals, such as air traffic controllers and truck drivers, who must visually track multiple moving objects, often while chronically sleep deprived. Support Supported by the Force Health Protection Program of the Office of Naval Research (SAA2402925-1, Contract Award no. N0001418IP00050).

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