scholarly journals A Threshold based Context Change Detection in Pervasive Environments: Application to a Smart Campus

2014 ◽  
Vol 32 ◽  
pp. 461-468 ◽  
Author(s):  
Nesrine Khabou ◽  
Ismael Bouassida Rodriguez ◽  
Ghada Gharbi ◽  
Mohamed Jmaiel
Keyword(s):  
Change Detection ◽  
Context Change ◽  
Pervasive Environments ◽  
Smart Campus

scholarly journals The Decay of Motor Memories Is Independent of Context Change Detection

2015 ◽  
Vol 11 (6) ◽  
pp. e1004278 ◽  
Author(s):  
Andrew E. Brennan ◽  
Maurice A. Smith
Keyword(s):  
Change Detection ◽  
Context Change

scholarly journals Context Change Detection for an Ultra-Low Power Low-Resolution Ego-Vision Imager

2016 ◽  
pp. 589-602 ◽  
Author(s):  
Francesco Paci ◽  
Lorenzo Baraldi ◽  
Giuseppe Serra ◽  
Rita Cucchiara ◽  
Luca Benini
Keyword(s):  
Low Power ◽  
Change Detection ◽  
Low Resolution ◽  
Context Change ◽  
Ultra Low Power

A context change detection approach for ubiquitous environments

2017 ◽  
Vol 10 (3) ◽  
pp. 320
Author(s):  
Nesrine Khabou ◽  
Ismael Bouassida Rodriguez ◽  
Mohamed Jmaiel
Keyword(s):  
Change Detection ◽  
Context Change ◽  
Detection Approach

A context change detection approach for ubiquitous environments

2017 ◽  
Vol 10 (3) ◽  
pp. 320
Author(s):  
Ismael Bouassida Rodriguez ◽  
Nesrine Khabou ◽  
Mohamed Jmaiel
Keyword(s):  
Change Detection ◽  
Context Change ◽  
Detection Approach

Vivid Imagers Are Better at Detecting Salient Changes

2006 ◽  
Vol 27 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Paul Rodway ◽  
Karen Gillies ◽  
Astrid Schepman
Keyword(s):  
Individual Differences ◽  
Change Detection ◽  
Visual Imagery ◽  
Detection Task ◽  
Level Of Detail ◽  
Detection Accuracy ◽  
Change Detection Task ◽  
Term Change ◽  
High Level

This study examined whether individual differences in the vividness of visual imagery influenced performance on a novel long-term change detection task. Participants were presented with a sequence of pictures, with each picture and its title displayed for 17  s, and then presented with changed or unchanged versions of those pictures and asked to detect whether the picture had been changed. Cuing the retrieval of the picture's image, by presenting the picture's title before the arrival of the changed picture, facilitated change detection accuracy. This suggests that the retrieval of the picture's representation immunizes it against overwriting by the arrival of the changed picture. The high and low vividness participants did not differ in overall levels of change detection accuracy. However, in replication of Gur and Hilgard (1975) , high vividness participants were significantly more accurate at detecting salient changes to pictures compared to low vividness participants. The results suggest that vivid images are not characterised by a high level of detail and that vivid imagery enhances memory for the salient aspects of a scene but not all of the details of a scene. Possible causes of this difference, and how they may lead to an understanding of individual differences in change detection, are considered.

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