Literature DB >> 23815479

Tracking by location and features: object correspondence across spatiotemporal discontinuities during multiple object tracking.

Frank Papenmeier1, Hauke S Meyerhoff2, Georg Jahn3, Markus Huff1.   

Abstract

We examined whether surface feature information is utilized to track the locations of multiple objects. In particular, we tested whether surface features and spatiotemporal information are weighted according to their availability and reliability. Accordingly, we hypothesized that surface features should affect location tracking across spatiotemporal discontinuities. Three kinds of spatiotemporal discontinuities were implemented across five experiments: abrupt scene rotations, abrupt zooms, and a reduced presentation frame rate. Objects were briefly colored across the spatiotemporal discontinuity. Distinct coloring that matched spatiotemporal information across the discontinuity improved tracking performance as compared with homogeneous coloring. Swapping distinct colors across the discontinuity impaired performance. Correspondence by color was further demonstrated by more mis-selected distractors appearing in a former target color than distractors appearing in a former distractor color in the swap condition. This was true even when color never supported tracking and when participants were instructed to ignore color. Furthermore, effects of object color on tracking occurred with unreliable spatiotemporal information but not with reliable spatiotemporal information. Our results demonstrate that surface feature information can be utilized to track the locations of multiple objects. This is in contrast to theories stating that objects are tracked based on spatiotemporal information only. We introduce a flexible-weighting tracking account stating that spatiotemporal information and surface features are both utilized by the location tracking mechanism. The two sources of information are weighted according to their availability and reliability. Surface feature effects on tracking are particularly likely when distinct surface feature information is available and spatiotemporal information is unreliable. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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Year:  2013        PMID: 23815479     DOI: 10.1037/a0033117

Source DB:  PubMed          Journal:  J Exp Psychol Hum Percept Perform        ISSN: 0096-1523            Impact factor:   3.332


  9 in total

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2.  Exploring the effectiveness of auditory, visual, and audio-visual sensory cues in a multiple object tracking environment.

Authors:  Julia Föcker; Polly Atkins; Foivos-Christos Vantzos; Maximilian Wilhelm; Thomas Schenk; Hauke S Meyerhoff
Journal:  Atten Percept Psychophys       Date:  2022-05-24       Impact factor: 2.157

3.  Decoding information about dynamically occluded objects in visual cortex.

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4.  The role of spatial configuration in multiple identity tracking.

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Review 5.  Multiple-target tracking in human and machine vision.

Authors:  Shiva Kamkar; Fatemeh Ghezloo; Hamid Abrishami Moghaddam; Ali Borji; Reza Lashgari
Journal:  PLoS Comput Biol       Date:  2020-04-09       Impact factor: 4.475

6.  Tracking multiple fish.

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Journal:  PeerJ       Date:  2022-03-03       Impact factor: 2.984

7.  Causality and continuity close the gaps in event representations.

Authors:  Jonathan F Kominsky; Lewis Baker; Frank C Keil; Brent Strickland
Journal:  Mem Cognit       Date:  2020-10-06

8.  Prediction processes during multiple object tracking (MOT): involvement of dorsal and ventral premotor cortices.

Authors:  Silke Atmaca; Waltraud Stadler; Anne Keitel; Derek V M Ott; Jöran Lepsien; Wolfgang Prinz
Journal:  Brain Behav       Date:  2013-10-03       Impact factor: 2.708

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

Authors:  James R H Cooke; Arjan C Ter Horst; Robert J van Beers; W Pieter Medendorp
Journal:  PLoS Comput Biol       Date:  2017-07-20       Impact factor: 4.475

  9 in total

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