Optics and Precision Engineering, Volume. 26, Issue 11, 2776(2018)
Template matching with multi-scale saliency
[1] [1] OUYANG W, TOMBARI F, MATTOCCIA S, et al.. Performance evaluation of full search equivalent pattern matching algorithms[J].IEEE Transactions on Pattern Analysis & Machine Intelligence, 2011, 34(1): 127-143.
[2] [2] ELBOHER E, WERMAN M. Asymmetric correlation: a noise robust similarity measure for template matching [J]. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2013, 22(8): 3062-3073.
[3] [3] HEL-OR Y, HEL-OR H, DAVID E. Matching by tone mapping: photometric invariant template matching [J].IEEE Transactions on Pattern Analysis & Machine Intelligence, 2013, 36(2): 317-330.
[4] [4] KORMAN S, REICHMAN D, TSUR G, et al.. FasT-match: fast affine template matching [C]. IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2013: 2331-2338.
[5] [5] TIAN Y, NARASIMHAN S G. Globally optimal estimation of nonrigid image distortion [J]. International Journal of Computer Vision, 2012, 98(3): 279-302.
[6] [6] DEKEL T, ORON S, RUBINSTEIN M, et al.. Best-buddies similarity for robust template matching [C]. Computer Vision and Pattern Recognition. IEEE, 2015: 2021-2029.
[7] [7] ORON S, DEKEL T, XUE T, et al.. Best-buddies similarity-robust template matching using mutual nearest neighbors [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-14.
[8] [8] TALMI I, MECHREZ R, ZELNIK-MANOR L. Template matching with deformable diversity similarity [C]. IEEE Conference on Computer Vision and Pattern Recognition. IEEE, 2017: 1311-1319.
[10] [10] JIANG H, WANG J, YUAN Z, et al.. Salient object detection: a discriminative regional feature integration approach [C]. Computer Vision and Pattern Recognition. IEEE, 2013: 2083-2090.
[11] [11] LAZEBNIK S, SCHMID C, PONCE J. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories [C]. Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. IEEE, 2006: 2169-2178.
[12] [12] GRAUMAN K, DARRELL T. Discriminative classification with sets of image features [C]. International Conference on Computer Vision, 2005.
[13] [13] WALLRAVEN C, CAPUTO B, GRAF A. Recognition with local features: the kernel recipe [C]. IEEE International Conference on Computer Vision. IEEE Computer Society, 2003: 257.
[14] [14] WILLAMOWSKI J, ARREGUI D, CSURKA G, et al.. Categorizing nine visual classes using local appearance descriptors [J]. Icpr Workshop on Learning for Adaptable Visual Systems, 2004.
[15] [15] ZHANG J, MARSZALEK M, LAZEBNIK S, et al.. Local features and kernels for classifcation of texture and object categories: An in-depth study [R]. Technical Report RR-5737, INRIA Rhne-Alpes, 2005.
[16] [16] HE K, ZHANG X, REN S, et al.. Spatial pyramid pooling in deep convolutional networks for visual recognition [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2014, 37(9): 1904-1916.
[19] [19] WU Y, LIM J, YANG M H. Online object tracking: a benchmark [C]. Computer Vision and Pattern Recognition. IEEE, 2013: 2411-2418.
[20] [20] SIMAKOV D, CASPI Y, SHECHTMAN E, et al.. Summarizing visual data using bidirectional similarity [C]. Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008: 1-8.
Get Citation
Copy Citation Text
LU Rui-qi, MA Hui-min. Template matching with multi-scale saliency[J]. Optics and Precision Engineering, 2018, 26(11): 2776
Category:
Received: Jun. 7, 2018
Accepted: --
Published Online: Jan. 10, 2019
The Author Email: Rui-qi LU (lurq17@mails.tsinghua.edu.cn)