
Colour combination attention for object recognition
Author(s) -
Zhu Jie,
Yu Jian,
Wang Chaomurilige,
Li FanZhang
Publication year - 2014
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2013.0431
Subject(s) - artificial intelligence , object (grammar) , histogram , pattern recognition (psychology) , computer science , computer vision , cognitive neuroscience of visual object recognition , feature (linguistics) , class (philosophy) , image (mathematics) , linguistics , philosophy
Within the bag‐of‐words (BOWs) framework, the multiple cues fusion methods provide excellent results in object and scene classification. Top‐down colour attention (CA) method is developed to use colour to guide attention by means of a top‐down category‐specific attention map. In this method, more features are taken from category‐specific colour regions where objects are more likely to be contained. In CA, the colours on the object are considered separately, so the diversity of object colours and large intra‐class colour variation make the discrimination of every colour on the object different. Object could be recognised as a collection of related colours. To enhance the object recognition capability of CA, our colour combination attention method uses mutual information and the colour combination histogram to estimate and combine the colours on the object. Results are presented on three challenging data sets, and the experiments demonstrate that the proposed feature fusion method significantly outperforms the state‐of‐the‐art methods.