scholarly journals The combinatorics of heuristic search termination for object recognition in cluttered environments

1991 ◽  
Vol 13 (9) ◽  
pp. 920-935 ◽  
Author(s):  
W.E.L. Grimson
Keyword(s):  
Object Recognition ◽  
Heuristic Search ◽  
Cluttered Environments ◽  
Search Termination

scholarly journals From Object Recognition to Object Localization

Robotics ◽  
2013 ◽  
pp. 53-68
Author(s):  
Rigas Kouskouridas ◽  
Antonios Gasteratos
Keyword(s):  
Object Recognition ◽  
Spatial Information ◽  
Image Understanding ◽  
Object Localization ◽  
Driver Assistance ◽  
Cluttered Environments ◽  
Working Space ◽  
Recent Advances ◽  
Pick And Place ◽  
Accurate Perception

Recognizing objects in a scene is a fundamental task in image understanding. The recent advances in robotics and related technologies have placed more challenges and stricter requirements to this issue. In such applications, robots must be equipped with a sense of location and direction with a view to the efficient accomplishment of navigation or demanding pick and place tasks. In addition, spatial information is required in surveillance processes where recognized targets are located in the working space of the robot. Furthermore, accurate perception of depth is mandatory in driver assistance applications. This chapter presents several recently proposed methods capable of first recognizing objects and then providing their spatial information in cluttered environments.

From Object Recognition to Object Localization

2012 ◽  
pp. 1-17
Author(s):  
Rigas Kouskouridas ◽  
Antonios Gasteratos
Keyword(s):  
Object Recognition ◽  
Spatial Information ◽  
Image Understanding ◽  
Object Localization ◽  
Driver Assistance ◽  
Cluttered Environments ◽  
Working Space ◽  
Recent Advances ◽  
Pick And Place ◽  
Accurate Perception

Recognizing objects in a scene is a fundamental task in image understanding. The recent advances in robotics and related technologies have placed more challenges and stricter requirements to this issue. In such applications, robots must be equipped with a sense of location and direction with a view to the efficient accomplishment of navigation or demanding pick and place tasks. In addition, spatial information is required in surveillance processes where recognized targets are located in the working space of the robot. Furthermore, accurate perception of depth is mandatory in driver assistance applications. This chapter presents several recently proposed methods capable of first recognizing objects and then providing their spatial information in cluttered environments.

Use It and Still Lose It?

GeroPsych ◽  
2010 ◽  
Vol 23 (3) ◽  
pp. 169-175 ◽  
Author(s):  
Adrian Schwaninger ◽  
Diana Hardmeier ◽  
Judith Riegelnig ◽  
Mike Martin
Keyword(s):  
Object Recognition ◽  
Cognitive Development ◽  
Recognition Test ◽  
Cognitive Aging ◽  
Recognition Task ◽  
Airport Security ◽  
Visual Object ◽  
Long Term Effects ◽  
Object Recognition Test ◽  
X Ray

In recent years, research on cognitive aging increasingly has focused on the cognitive development across middle adulthood. However, little is still known about the long-term effects of intensive job-specific training of fluid intellectual abilities. In this study we examined the effects of age- and job-specific practice of cognitive abilities on detection performance in airport security x-ray screening. In Experiment 1 (N = 308; 24–65 years), we examined performance in the X-ray Object Recognition Test (ORT), a speeded visual object recognition task in which participants have to find dangerous items in x-ray images of passenger bags; and in Experiment 2 (N = 155; 20–61 years) in an on-the-job object recognition test frequently used in baggage screening. Results from both experiments show high performance in older adults and significant negative age correlations that cannot be overcome by more years of job-specific experience. We discuss the implications of our findings for theories of lifespan cognitive development and training concepts.

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