Visual Surveillance for Aircraft Activity Monitoring

Author(s):  
D. Thirde ◽  
M. Borg ◽  
J. Ferryman ◽  
V. Valentin ◽  
F. Fusier ◽  
...  
2009 ◽  
Vol 14 (2) ◽  
pp. 142-152 ◽  
Author(s):  
Johannes B.J. Bussmann ◽  
Ulrich W. Ebner-Priemer ◽  
Jochen Fahrenberg

Behavior is central to psychology in almost any definition. Although observable activity is a core aspect of behavior, assessment strategies have tended to focus on emotional, cognitive, or physiological responses. When physical activity is assessed, it is done so mostly with questionnaires. Converging evidence of only a moderate association between self-reports of physical activity and objectively measured physical activity does raise questions about the validity of these self-reports. Ambulatory activity monitoring, defined as the measurement strategy to assess physical activity, posture, and movement patterns continuously in everyday life, has made major advances over the last decade and has considerable potential for further application in the assessment of observable activity, a core aspect of behavior. With new piezoresistive sensors and advanced computer algorithms, the objective measurement of physical activity, posture, and movement is much more easily achieved and measurement precision has improved tremendously. With this overview, we introduce to the reader some recent developments in ambulatory activity monitoring. We will elucidate the discrepancies between objective and subjective reports of activity, outline recent methodological developments, and offer the reader a framework for developing insight into the state of the art in ambulatory activity-monitoring technology, discuss methodological aspects of time-based design and psychometric properties, and demonstrate recent applications. Although not yet main stream, ambulatory activity monitoring – especially in combination with the simultaneous assessment of emotions, mood, or physiological variables – provides a comprehensive methodology for psychology because of its suitability for explaining behavior in context.


2012 ◽  
Author(s):  
Lyndsey K. Lanagan-Leitzel ◽  
Emily Skow ◽  
Cathleen M. Moore

Author(s):  
Tannistha Pal

Images captured in severe atmospheric catastrophe especially in fog critically degrade the quality of an image and thereby reduces the visibility of an image which in turn affects several computer vision applications like visual surveillance detection, intelligent vehicles, remote sensing, etc. Thus acquiring clear vision is the prime requirement of any image. In the last few years, many approaches have been made towards solving this problem. In this article, a comparative analysis has been made on different existing image defogging algorithms and then a technique has been proposed for image defogging based on dark channel prior strategy. Experimental results show that the proposed method shows efficient results by significantly improving the visual effects of images in foggy weather. Also computational time of the existing techniques are much higher which has been overcame in this paper by using the proposed method. Qualitative assessment evaluation is performed on both benchmark and real time data sets for determining theefficacy of the technique used. Finally, the whole work is concluded with its relative advantages and shortcomings.


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