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Computer Vision and Image Understanding
Academic Press, Inc.
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Free-hand sketch recognition by multi-kernel feature learning
Li Y., Hospedales T., Song Y., Gong S. Computer Vision and Image Understanding 137(C): 1-11, 2015. Type: Article
Touchscreen devices, or even electronic stylus writing instruments (for example, Apple Pencils), are becoming increasingly common nowadays. Drawing sketches is something humans have done to communicate since ancient times. Sketches can...
Oct 8 2015
Visual topic network: building better image representations for images in social media
Niu Z., Hua G., Tian Q., Gao X. Computer Vision and Image Understanding 136(C): 3-13, 2015. Type: Article
Topic networks deal with developing image representations using image features, for example, bag-of-words representations. However, the representation of social media images (or social images) and the web’s visual contents, c...
Sep 8 2015
Random walks in directed hypergraphs and application to semi-supervised image segmentation
Ducournau A., Bretto A. Computer Vision and Image Understanding 12091-102, 2014. Type: Article
Hypergraphs are generalizations of graphs. In conventional graphs, the vertex set is partitioned into a number of pairs called edges. In hypergraphs, the vertex set is partitioned into a number of hyperedges with possibly more than two...
Jul 14 2015
TouchCut: fast image and video segmentation using single-touch interaction
Wang T., Han B., Collomosse J. Computer Vision and Image Understanding 12014-30, 2014. Type: Article
Have you ever used the magic wand tool in Photoshop? If so, it accomplishes 90 percent of the work described in this paper. The only difference is that this work uses finger touch instead of a mouse click, thanks to the prevailing touc...
Jun 9 2015
Efficient semantic image segmentation with multi-class ranking prior
Pei D., Li Z., Ji R., Sun F. Computer Vision and Image Understanding 12081-90, 2014. Type: Article
Image segmentation is the process of separating an image into object and nonobject components. Computer vision applications like medical and biomedical imaging, satellite imaging, robot navigation, and image retrieval are based on the ...
Apr 15 2014
Hough-based tracking of non-rigid objects
Godec M., Roth P., Bischof H. Computer Vision and Image Understanding 117(10): 1245-1256, 2013. Type: Article
Godec et al. use Hough forests and ferns for online object tracking in images. They implement voting-based detection and back-projection and a rough GrabCut segmentation approach, removing the bounding box representation of the non-rig...
Jan 9 2014
Manifold surface reconstruction of an environment from sparse structure-from-motion data
Lhuillier M., Yu S. Computer Vision and Image Understanding 117(11): 1628-1644, 2013. Type: Article
It is nice to see a method that can reconstruct a 3D scene using sparse input instead of dense input to achieve better performance for computation time and spatial complexities....
Nov 27 2013
Comparison of mid-level feature coding approaches and pooling strategies in visual concept detection
Koniusz P., Yan F., Mikolajczyk K. Computer Vision and Image Understanding 117(5): 479-492, 2013. Type: Article
The paper makes a systematic and detailed evaluation of two main stages of bag-of-words (BoW) modeling for computer vision. BoW is an accepted technique in computer vision to represent vocabularies of image features. The authors explor...
Jul 26 2013
Probabilistic cost model for nearest neighbor search in image retrieval
Kim K., Hasan M., Heo J., Tai Y., Yoon S. Computer Vision and Image Understanding 116(9): 991-998, 2012. Type: Article
Use of the Internet for retrieving images has gained considerable momentum. Searching the Internet for images based on content is an important task, not only in engineering but also for regular Internet users. Due to technological deve...
Oct 29 2012
Local binary patterns for multi-view facial expression recognition
Moore S., Bowden R. Computer Vision and Image Understanding 115(4): 541-558, 2011. Type: Article
Local binary patterns (LBPs) are a popular method in texture characterization. LBPs provide remarkable results under taxing situations, such as scale-, illumination-, and rotation-invariant recognition. Human emotion recognition throug...
Nov 29 2011
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