Fast repetition detection in TV streams using duration patterns

Abstract The literature has mixed reports on whether the N170, an early visual ERP response to words, signifies orthographic and/or phonological processing, and whether these effects are moderated by script and language expertise. In this study, native Chinese readers, Japanese–Chinese, and Korean–Chinese bilingual readers performed a one-back repetition detection task with single Chinese characters that differed in phonological regularity status. Results using linear mixed effects models showed that Korean–Chinese readers had bilateral N170 response, while native Chinese and Japanese–Chinese groups had left-lateralized N170, with stronger left lateralization in native Chinese than Japanese–Chinese readers. Additionally, across groups, irregular characters had bilateral increase in N170 amplitudes compared to regular characters. These results suggested that visual familiarity to a script rather than orthography-phonology mapping determined the left lateralization of the N170 response, while there was automatic access to sublexical phonology in the N170 time window in native and non-native readers alike.

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Left-lateralized N170 Effects of Visual Expertise in Reading: Evidence from Japanese Syllabic and Logographic Scripts

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2008.20125 ◽

2008 ◽

Vol 20 (10) ◽

pp. 1878-1891 ◽

Cited By ~ 89

Author(s):

Urs Maurer ◽

Jason D. Zevin ◽

Bruce D. McCandliss

Keyword(s):

Event Related Potential ◽

Visual Word ◽

Writing Systems ◽

Visual Expertise ◽

Native Japanese Speakers ◽

Visual Words ◽

Repetition Detection ◽

N170 Component ◽

Word Forms ◽

Series Of Experiments

The N170 component of the event-related potential (ERP) reflects experience-dependent neural changes in several forms of visual expertise, including expertise for visual words. Readers skilled in writing systems that link characters to phonemes (i.e., alphabetic writing) typically produce a left-lateralized N170 to visual word forms. This study examined the N170 in three Japanese scripts that link characters to larger phonological units. Participants were monolingual English speakers (EL1) and native Japanese speakers (JL1) who were also proficient in English. ERPs were collected using a 129-channel array, as participants performed a series of experiments viewing words or novel control stimuli in a repetition detection task. The N170 was strongly left-lateralized for all three Japanese scripts (including logographic Kanji characters) in JL1 participants, but bilateral in EL1 participants viewing these same stimuli. This demonstrates that left-lateralization of the N170 is dependent on specific reading expertise and is not limited to alphabetic scripts. Additional contrasts within the moraic Katakana script revealed equivalent N170 responses in JL1 speakers for familiar Katakana words and for Kanji words transcribed into novel Katakana words, suggesting that the N170 expertise effect is driven by script familiarity rather than familiarity with particular visual word forms. Finally, for English words and novel symbol string stimuli, both EL1 and JL1 subjects produced equivalent responses for the novel symbols, and more left-lateralized N170 responses for the English words, indicating that such effects are not limited to the first language. Taken together, these cross-linguistic results suggest that similar neural processes underlie visual expertise for print in very different writing systems.

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Fast and accurate audio repetition detection in broadcast audio/video towards applications of content-based intelligent radio/TV services

2011 6th International Conference on Pervasive Computing and Applications ◽

10.1109/icpca.2011.6106559 ◽

2011 ◽

Cited By ~ 1

Author(s):

Xiangdong Wang ◽

Xinhui Li ◽

Yang Gao ◽

Ying Yang ◽

Yueliang Qian

Keyword(s):

Repetition Detection ◽

Audio Video

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TEMPORAL REPETITION DETECTION FOR GROUND VISIBILITY ASSESSMENT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-2-2020-829-2020 ◽

2020 ◽

Vol V-2-2020 ◽

pp. 829-835

Author(s):

R. Grompone von Gioi ◽

C. Hessel ◽

T. Dagobert ◽

J. M. Morel ◽

C. de Franchis

Keyword(s):

Satellite Image ◽

Detection Methods ◽

Cloud Detection ◽

Satellite Constellations ◽

Repetition Detection ◽

Spectral Bands ◽

Alternative Approach ◽

Earth Observation Satellite ◽

Satellite Image Analysis ◽

Local Image

Abstract. Assessing ground visibility is a crucial step in automatic satellite image analysis. Nevertheless, several recent Earth observation satellite constellations lack specially designed spectral bands and use a frame camera, precluding spectrum-based and parallax-based cloud detection methods. An alternative approach is to detect the parts of each image where the ground is visible. This can be done by comparing locally pairs of registered images in a temporal series: matching regions are necessarily cloud free. Indeed, the ground has persistent patterns that can be observed repetitively in the time series while the appearance of clouds changes at each date. To detect reliably the “visible” ground, we propose here an a contrario local image matching method coupled with an efficient greedy algorithm.

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Repetition detection and rapid auditory learning for stochastic tone clouds

10.31234/osf.io/3uzs2 ◽

2021 ◽

Author(s):

Trevor Agus ◽

Daniel Pressnitzer

Keyword(s):

Amplitude Modulation ◽

Task Difficulty ◽

Full Range ◽

Auditory Memory ◽

Perceptual Range ◽

Experimental Conditions ◽

Auditory Learning ◽

Rapid Learning ◽

Repetition Detection ◽

Neurophysiological Studies

Stochastic sounds are useful to probe auditory memory, as they require listeners to learn unpredictable and novel patterns under controlled experimental conditions. Previous studies using white noise or random click trains have demonstrated rapid auditory learning for instances of such a class of sounds. Here, we tested stochastic sounds that enabled parametrical control of spectrotemporal complexity: tone clouds. Tone clouds were defined as broadband combinations of tone pips at randomized frequencies and onset times. Varying the density of tones covered a perceptual range from random melodies to noise. Results showed that listeners could detect repeating patterns in tone clouds at all tested densities, with sparse tone clouds being the easiest. A model estimating amplitude modulation within cochlear filters showed that repetition detection was correlated with the amount of amplitude modulation at lower rates. Rapid learning of individual tone clouds was also observed, again for all densities. Tone clouds thus provide a tool to probe auditory learning in a variety of task-difficulty settings, which could be useful for clinical or neurophysiological studies. They also show that rapid auditory learning operates over the full range of spectrotemporal complexity typical of natural sounds, essentially from melodies to noise.

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