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Qun Li
Beijing University of Posts and Telecommunications
4Publications
2H-index
28Citations
Publications 4
Newest
Sep 1, 2013 in ICIP (International Conference on Image Processing)
#1Qun Li (Beijing University of Posts and Telecommunications)H-Index: 2
#2Zhen Qin (UCR: University of California, Riverside)H-Index: 7
Last.Bir Bhanu (UCR: University of California, Riverside)H-Index: 47
view all 6 authors...
Reference-based image classification approach introduces a reference-set for both image representation and dictionary learning. It significantly reduces the dimensionality of represented images and shows outstanding performance even with randomly selected reference images and simple distance measure. In this paper, we improve upon existing work with two major contributions. First, we show that a more representative reference-set contributes to better classification accuracy. To this end, we care...
1 CitationsSource
Sep 1, 2013 in ICIP (International Conference on Image Processing)
#1Lunshao Chai (Beijing University of Posts and Telecommunications)H-Index: 4
#2Zhen Qin (UCR: University of California, Riverside)H-Index: 7
Last.Jun Guo (Beijing University of Posts and Telecommunications)H-Index: 11
view all 5 authors...
In this paper, we enhance the Shape Context-based descriptor, shapemes, by introducing an ordered bag-of-features model and dynamic programming. The proposed descriptor consists of a series of sub-histograms of shapemes, each of which represents a subset of sampled points. The division of the sampled points is based on their sequential positions on the contour of the shape, so the representation has intrinsic order and is therefore named ordered histogram of shapemes. Then dynamic programming is...
4 CitationsSource
#1Qun Li (Beijing University of Posts and Telecommunications)H-Index: 2
#2Honggang Zhang (Beijing University of Posts and Telecommunications)H-Index: 14
Last.Le An (UCR: University of California, Riverside)H-Index: 18
view all 5 authors...
A reference-based algorithm for scene image categorization is presented in this letter. In addition to using a reference-set for images representation, we also associate the reference-set with training data in sparse codes during the dictionary learning process. The reference-set is combined with the reconstruction error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. After dictionaries are constructed, Locality-constrained Linear Cod...
22 CitationsSource
Sep 1, 2012 in ICIP (International Conference on Image Processing)
#1Qun Li (Beijing University of Posts and Telecommunications)H-Index: 2
#2Honggang Zhang (Beijing University of Posts and Telecommunications)H-Index: 14
Last.Bir Bhanu (UCR: University of California, Riverside)H-Index: 47
view all 5 authors...
Visual codebook based quantization of robust appearance descriptors extracted from local image patches is an effective means of capturing image statistics for texture analysis and natural scene classification. In this paper, based on the newly proposed statistics of word activation forces (WAFs), we optimize the codebook. Currently, codebooks are typically created from a set of training images using a clustering algorithm. However, these codebooks are often functionally limited due to redundancy...
1 CitationsSource
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