Scene Understanding: A Framework for Image Segmentation via Object Recognition

2010 ◽  
Author(s):  
Kar Seng Loke ◽  
Simon Egerton
Keyword(s):  
Image Segmentation ◽  
Object Recognition ◽  
Scene Understanding

Multiband Image Segmentation and Object Recognition for Understanding Road Scenes

2011 ◽  
Vol 12 (4) ◽  
pp. 1423-1433 ◽  
Author(s):  
Yousun Kang ◽  
Koichiro Yamaguchi ◽  
Takashi Naito ◽  
Yoshiki Ninomiya
Keyword(s):  
Image Segmentation ◽  
Object Recognition

Does context or color improve object recognition in patients with low vision?

2008 ◽  
Vol 25 (5-6) ◽  
pp. 685-691 ◽  
Author(s):  
MURIEL BOUCART ◽  
PASCAL DESPRETZ ◽  
KATRINE HLADIUK ◽  
THOMAS DESMETTRE
Keyword(s):  
Image Segmentation ◽  
Object Recognition ◽  
Low Vision ◽  
Object Perception ◽  
Age Related Macular Degeneration ◽  
Natural Scenes ◽  
Gray Level ◽  
Spatial Properties ◽  
Age Related ◽  
Complex Stimuli

AbstractMost studies on people with age-related macular degeneration (AMD) have been focused on investigations of low-level processes with simple stimuli like gratings, letters, and in perception of isolated faces or objects. We investigated the ability of people with low vision to analyze more complex stimuli like photographs of natural scenes. Fifteen participants with AMD and low vision (acuity on the better eye <20/200) and 11 normally sighted age-matched controls took part in the study. They were presented with photographs of either colored or achromatic gray level scenes in one condition and with photographs of natural scenes versus isolated objects extracted from these scenes in another condition. The photographs were centrally displayed for 300 ms. In both conditions, observers were instructed to press a key when they saw a predefined target (a face or an animal). The target was present in half of the trials. Color facilitated performance in people with low vision, while equivalent performance was found for colored and achromatic pictures in normally sighted participants. Isolated objects were categorized more accurately than objects in scenes in people with low vision. No difference was found for normally sighted observers. The results suggest that spatial properties that facilitate image segmentation (e.g., color and reduced crowding) help object perception in people with low vision.

Image segmentation and object recognition based on bidirectional scanning fusion technique

2009 ◽  
Author(s):  
Hao-peng Xu ◽  
Wuqin Toing ◽  
Wei-liang Fan ◽  
Jin-yu Xiong
Keyword(s):  
Image Segmentation ◽  
Object Recognition ◽  
Fusion Technique
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