Object recognition with multiple cues

This work describes a method to allow objects for autonomous robot navigation on outdoor environment. The proposition of the method segments and recognizes the object from an image taken by moving robot on outdoor environment. We classify the object natural and artificial. We classify trees as natural objects and buildings as artificial objects. Then we define their characteristics individually. In the process, we segment objects included by preprocessing using multiple cues and show the method of segmentation based on low-level features using multiple cues. Multiple cues are color, line segment, context information, HCM (Hue Co-occurrence Matrix), PCs (Principal Components), vanishing point. Objects can be recognized when we combine predefined multiple cues. The correct object recognition of proposed system is over 92% among our test database which consist of about 1200 images. We accomplish the result of image segmentation using multiple cues and object recognition through experiments.

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Towards using multiple cues for robust object recognition

Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems - AAMAS '07 ◽

10.1145/1329125.1329354 ◽

2007 ◽

Cited By ~ 7

Author(s):

Sarah Aboutalib ◽

Manuela Veloso

Keyword(s):

Object Recognition ◽

Multiple Cues

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Use It and Still Lose It?

GeroPsych ◽

10.1024/1662-9647/a000020 ◽

2010 ◽

Vol 23 (3) ◽

pp. 169-175 ◽

Cited By ~ 14

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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