scholarly journals The dynamics of audio-visual integration capacity as a function of environmental difficulty, stimulus factors, and experience

2021 ◽  
Author(s):  
Jonathan Michael Paul Wilbiks
Keyword(s):  
Working Memory ◽  
Object Tracking ◽  
Fluid Dynamic ◽  
Real Life ◽  
Multiple Object Tracking ◽  
Audiovisual Integration ◽  
Future Research ◽  
Science Literature ◽  
Environmental Complexity ◽  
Multiple Object

The capacities of unimodal processes such as visual and auditory working memory, multiple object tracking, and attention have been heavily researched in the psychological science literature. In recent years there has been an increase in the amount of research into multimodal processes such as the integration of auditory and visual stimuli, but to my knowledge, there has only been a single published article to date investigating the capacity of audiovisual integration, which found that the capacity of audiovisual integration is limited to a single item. The purpose of this dissertation is to elucidate some of the factors that contribute to the capacity of audiovisual integration, and to illustrate that the interaction of these respective factors makes the capacity a fluid, dynamic property. Chapter 1 reviews the literature coming from multimodal integration research, as well as from unimodal topics that are pertinent to the factors that are being manipulated in the dissertation: namely, working memory, multiple object tracking, and attention. Chapter 2 considers the paradigmatic structure employed by the single study on audiovisual integration capacity and breaks down the component factors of proactive interference and temporal predictability, which contribute to the environmental complexity of the scenario, in the first illustration of the flexibility of capacity of audiovisual integration. Chapter 3 explores the effects of stimulus factors, considering the effects of crossmodal congruency and perceptual chunking on audiovisual integration capacity. Chapter 4 explores the variability of audiovisual integration capacity within an individual over time by means of a training study. Chapter 5 summarizes the findings of the research within, discusses some overarching themes with regard to audiovisual integration capacity including how information is processed through integration and how these findings could be applied to real-life scenarios, suggests some avenues for future research such as further manipulations of modality and SOA, and draws conclusions and answers to the research questions. This research extends what is known about audiovisual integration capacity, both in terms of its numerical value and the factors that play a role in its establishment. It also demonstrates that there is no overarching limitation on the capacity of audiovisual integration, as the initial paper on this topic suggests, but rather that it is a process subject to multiple factors, and can be changed depending on the situation in which integration is occurring.

scholarly journals The dynamics of audio-visual integration capacity as a function of environmental difficulty, stimulus factors, and experience

2021 ◽  
Author(s):  
Jonathan Michael Paul Wilbiks
Keyword(s):  
Working Memory ◽  
Object Tracking ◽  
Fluid Dynamic ◽  
Real Life ◽  
Multiple Object Tracking ◽  
Audiovisual Integration ◽  
Future Research ◽  
Science Literature ◽  
Environmental Complexity ◽  
Multiple Object

The capacities of unimodal processes such as visual and auditory working memory, multiple object tracking, and attention have been heavily researched in the psychological science literature. In recent years there has been an increase in the amount of research into multimodal processes such as the integration of auditory and visual stimuli, but to my knowledge, there has only been a single published article to date investigating the capacity of audiovisual integration, which found that the capacity of audiovisual integration is limited to a single item. The purpose of this dissertation is to elucidate some of the factors that contribute to the capacity of audiovisual integration, and to illustrate that the interaction of these respective factors makes the capacity a fluid, dynamic property. Chapter 1 reviews the literature coming from multimodal integration research, as well as from unimodal topics that are pertinent to the factors that are being manipulated in the dissertation: namely, working memory, multiple object tracking, and attention. Chapter 2 considers the paradigmatic structure employed by the single study on audiovisual integration capacity and breaks down the component factors of proactive interference and temporal predictability, which contribute to the environmental complexity of the scenario, in the first illustration of the flexibility of capacity of audiovisual integration. Chapter 3 explores the effects of stimulus factors, considering the effects of crossmodal congruency and perceptual chunking on audiovisual integration capacity. Chapter 4 explores the variability of audiovisual integration capacity within an individual over time by means of a training study. Chapter 5 summarizes the findings of the research within, discusses some overarching themes with regard to audiovisual integration capacity including how information is processed through integration and how these findings could be applied to real-life scenarios, suggests some avenues for future research such as further manipulations of modality and SOA, and draws conclusions and answers to the research questions. This research extends what is known about audiovisual integration capacity, both in terms of its numerical value and the factors that play a role in its establishment. It also demonstrates that there is no overarching limitation on the capacity of audiovisual integration, as the initial paper on this topic suggests, but rather that it is a process subject to multiple factors, and can be changed depending on the situation in which integration is occurring.

scholarly journals Individual differences in multiple object tracking, attentional cueing, and age account for variability in the capacity of audiovisual integration

2020 ◽  
Author(s):  
Jonathan Wilbiks ◽  
Annika Beatteay
Keyword(s):  
Individual Differences ◽  
Object Tracking ◽  
Memory Task ◽  
Multiple Object Tracking ◽  
Audiovisual Integration ◽  
Future Research ◽  
Attention Network Test ◽  
Test Experiment ◽  
Multiple Object ◽  
Health Differences

There has been a recent increase in individual differences research within the field of audio-visual perception (Spence & Squire, 2003), and furthering the understanding of audiovisual integration capacity with an individual differences approach is an important facet within this line of research. Across four experiments, participants were asked to complete an audiovisual integration capacity task (cf. Van der Burg et al., 2013; Wilbiks & Dyson, 2016; 2018), along with differing combinations of additional perceptual tasks. Experiment 1 employed a multiple object tracking task and a visual working memory task. Experiment 2 compared performance on the capacity task with that of the attention network test. Experiment 3 examined participants’ focus in space through a Navon task and vigilance through time. Having completed this exploratory work, in Experiment 4 we collected data again from the tasks that were found to correlate significantly across the first three experiments and entered them into a regression model to predict capacity. The current research provides a preliminary explanation of the vast individual differences seen in audiovisual integration capacity in previous research, showing that by considering an individual’s multiple object tracking span, focus in space, and attentional factors, we can account for up to 34.3% of the observed variation in capacity. Future research should seek to examine higher-level differences between individuals that may contribute to audiovisual integration capacity, including neurodevelopmental and mental health differences.

scholarly journals MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking

2020 ◽  
Author(s):  
Patrick Dendorfer ◽  
Aljos̆a Os̆ep ◽  
Anton Milan ◽  
Konrad Schindler ◽  
Daniel Cremers ◽  
...  
Keyword(s):  
Object Tracking ◽  
State Of The Art ◽  
Objective Measure ◽  
Multiple Object Tracking ◽  
Future Research ◽  
Single Camera ◽  
Multiple Object ◽  
Future Research Directions ◽  
Self Driving Cars ◽  
Measure Of Performance

AbstractStandardized benchmarks have been crucial in pushing the performance of computer vision algorithms, especially since the advent of deep learning. Although leaderboards should not be over-claimed, they often provide the most objective measure of performance and are therefore important guides for research. We present MOTChallenge, a benchmark for single-camera Multiple Object Tracking (MOT) launched in late 2014, to collect existing and new data and create a framework for the standardized evaluation of multiple object tracking methods. The benchmark is focused on multiple people tracking, since pedestrians are by far the most studied object in the tracking community, with applications ranging from robot navigation to self-driving cars. This paper collects the first three releases of the benchmark: (i) MOT15, along with numerous state-of-the-art results that were submitted in the last years, (ii) MOT16, which contains new challenging videos, and (iii) MOT17, that extends MOT16 sequences with more precise labels and evaluates tracking performance on three different object detectors. The second and third release not only offers a significant increase in the number of labeled boxes, but also provide labels for multiple object classes beside pedestrians, as well as the level of visibility for every single object of interest. We finally provide a categorization of state-of-the-art trackers and a broad error analysis. This will help newcomers understand the related work and research trends in the MOT community, and hopefully shed some light into potential future research directions.

scholarly journals Examining the roles of working memory and visual attention in multiple object tracking expertise

2020 ◽  
Vol 21 (2) ◽  
pp. 209-222
Author(s):  
David J. Harris ◽  
Mark R. Wilson ◽  
Emily M. Crowe ◽  
Samuel J. Vine
Keyword(s):  
Working Memory ◽  
Visual Attention ◽  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Object

scholarly journals Tracking of moving players in soccer: Multiple object tracking in real-life environment

2018 ◽  
Vol 18 (10) ◽  
pp. 728
Author(s):  
Lauri Oksama ◽  
Teemu Leino ◽  
Jukka Hyönä
Keyword(s):  
Object Tracking ◽  
Real Life ◽  
Multiple Object Tracking ◽  
Multiple Object

The effects of colour complexity and similarity on multiple object tracking performance

2018 ◽  
Vol 72 (8) ◽  
pp. 1903-1912 ◽  
Author(s):  
Chundi Wang ◽  
Luming Hu ◽  
Thomas Talhelm ◽  
Xuemin Zhang
Keyword(s):  
Working Memory ◽  
Object Tracking ◽  
Visual Working Memory ◽  
Multiple Object Tracking ◽  
Tracking Performance ◽  
Surface Features ◽  
Attentional Resources ◽  
Multiple Object ◽  
Target Set ◽  
Distinct Features

Surface features can be used during multiple object tracking (MOT). Previous studies suggested that surface features might be stored in visual working memory to assist object tracking, and attentive tracking and visual working memory share common attentional resources. However, it is still unknown whether features of both the target and distractor sets will be stored, or features of the target and distractor sets are processed differently. Moreover, how feature distinctiveness and similarity between the target and distractor sets affect tracking and allocation of attentional resources are still not clear. First, we manipulated the colour complexity of the target set (CT) and the colour complexity of the distractor set (CD), respectively, in two experiments, where colours of the target and distractor sets were always distinct, to test their effects on tracking performance. If features of the target and distractor sets are stored, manipulating feature complexity of the target and distractor sets would significantly affect tracking performance. Second, this study tested whether tracking performance was affected by different levels of distinctiveness between the target and distractor sets (DTD) and explored how distinctiveness affected tracking and allocation of attentional resources. Results showed that DTD and CT significantly affect tracking performance and allocation of attentional resources, but not CD. These results indicated that when targets and distractors have distinct features, only the surface features of the targets are maintained in visual working memory. And when targets have the same colour with the distractors, they are more difficult and consume more attentional resources to track.

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