JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (2): 14-21.doi: 10.6040/j.issn.1672-3961.2.2015.065

Previous Articles     Next Articles

Object classification method based on component pyramid matching

ZHU Jie1,2, WANG Jing1, LIU Fei3, GAO Guandong1, DUAN Qing1   

  1. 1. Department of Information Management, The Central Institute for Correctional Police, Baoding 071000, Heibei, China;
    2. Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
    3. Modern Educational Technology Center, The Central Institute for Correctional Police, Baoding 071000, Heibei, China
  • Received:2015-05-16 Online:2016-04-20 Published:2015-05-16

PDF (PC)

797

Abstract: The image representation method based on component pyramid matching(CPM)was proposed, which separated the patches into different levels based on colors. In each level, some colors were selected by the optimal color selection method, then the patches with these selected colors were considered as the foreground components, and the rest of the patches with other colors were considered as the background components. Usually, the foreground components corresponded to some parts of the objects, which could supply weak semantic information for the image representation. Then, the background components were split into the foreground and background components in the next level based on the similar color selection method. The final representation of an image was obtained by concatenating the component histograms in each level. Classification results were presented on Soccer, Flower17 and Flower102 datasets, and the experiments showed that CMP could obtain satisfactory results in these datasets.

Key words: level, image representation, classification, component pyramid matching, color

CLC Number: 

  • TP301
[1] CSURKA G, DANCE CR, FAN LX, et al. Visual categorization with bags of keypoints[C] //Proceedings of the 8th European Conference on Computer Vision. Prague: IEEE, 2004:1-22.
[2] CAO Y, WANG C, LI Z, et al. Spatial-bag-of-features[C] //Proceedings of the 23th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010:3352-3359.
[3] MORIOKA N, SATOH S. Building compact local pairwise codebook with joint feature space clustering[C] //Proceedings of the 11th European Conference on Computer Vision. Crete: IEEE, 2010:692-705.
[4] SIVIC J, RUSSELL B, EFROS A, et al. Discovering objects and their location in images[C] //Proceedings of the 10th International Conference on Computer Vision. Beijing:IEEE, 2005:370-377.
[5] GRAUMAN K, DARRELL T. The pyramid match kernel: Discriminative classification with sets of image features[C] //Proceedings of the 10th International Conference on Computer Vision. Beijing: IEEE, 2005:1458-1465.
[6] LAZEBNIK S, SCHMID C, PONCE J. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories[C] //Proceedings of the 19th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York:IEEE, 2006:2169-2178.
[7] YANG J, YU K, GONG Y, et al. Linear spatial pyramid matching using sparse coding for image classification [C] //Proceedings of the 22th IEEE Computer Society Conference on Computer Vision and Pattern Recognition.Florida: IEEE, 2009:1794-1801.
[8] LI F, CARREIRA J, SMINCHISESCU C. Object recognition as ranking holistic figure-ground hypotheses[C] //Proceedings of the 23th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010:1712-1719.
[9] CHEN Q, SONG Z, HUA Y, et al. Hierarchical matching with side information for image classification[C] //Proceedings of the 25th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Rhode Island: IEEE, 2012:3426-3433.
[10] LI L J, SU H, LIM Y, et al. Object bank: an object-level image representation for high-level visual recognition[J].International Journal of Computer Vision, 2014, 107(1):20-39.
[11] FERNANDO B, FROMONT E, TUYTELAARS T. Mining mid-level features for image classification[J]. International Journal of Computer Vision, 2014, 108(3): 186-203.
[12] LIU J, ZHANG C, TIAN Q, et al. One step beyond bags of features: visual categorization using component[C] //Proceedings of the International Conference on Image Processing. Brussels: IEEE, 2011:2417-2420.
[13] LOWE D G. Object recognition from local scale-invariant features[C] //Proceedings of the 7th International Conference on Computer Vision. Kerkyra:IEEE, 1999: 1150-1157.
[14] VAN-DE-WEIJER J, SCHMID C, VERBEEK J, et al. Learning color names for real-world applications[J].IEEE Transactions on Image Processing, 2009, 18(7):1512-1523.
[15] VAN-DE-WEIJER J, SCHMID C. Coloring local feature extraction[C] //Proceedings of the 9th European Conference on Computer Vision. Graz: IEEE, 2006:334-348.
[16] SHAHBAZ-KHAN F, VAN-DE-WEIJER J, VANRELL M.Top-down color attention for object recognition[C] //Proceedings of the 12th International Conference on Computer Vision. Tokyo: IEEE, 2009:979-986.
[17] NILSBACK M E, ZISSEMAN A. A visual vocabulary for flower classification[C] //Proceedings of the 19th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2006:1447-1454.
[18] NILSBACK M E, ZISSERMAN A. Automated flower classification over a large number of classes[C] //Proceedings of the 6th Indian Conference on Computer Vision, Graphics and Image Processing. Bhubaneswar: IEEE, 2008:722-729.
[19] FERNANDO B, FROMONT E, MUSELET D, et al. Discriminative feature fusion for image classification[C] //Proceedings of the 25th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Rhode Island: IEEE, 2012:3434-3441.
[20] GEHLER P, NOWOZIN S. On feature combination for multiclass object classification[C] //Proceedings of the 12th International Conference on Computer Vision. Tokyo:IEEE, 221-228.
[21] YUAN X T, YAN S. Visual classification with multi-task joint sparse representation[C] //Proceedings of the 23th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010:3493-3500.
[22] YAN F, MIKOLAJCZYK K, BARNARD M, et al. Lp norm multiple kernel fisher discriminant analysis for object and image categorisation[C] //Proceedings of the 23th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010:3626-3632.
[23] KANAN C, COTTRELL G. Robust classification of objects, faces, and flowers using natural image statistics [C] //Proceedings of the 23th IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010:2472-2479.
[24] CHAI Y, LEMPITSKY V, ZISSERMAN A. BiCoS: A Bi-level Co-Segmentation Method for Image Classification[C] //Proceedings of the 13th International Conference on Computer Vision. Barcelona: IEEE, 2011:2579-2586.
[25] CHAI Y, RAHTU E, RAHTU E, et al. Tricos: A tri-level class-discriminative co-segmentation method for image classification[C] //Proceedings of the 12th European Conference on Computer Vision. Firenze: IEEE, 2012:794-807.
[1] ZHOU Qian, LI Qun, ZHU Dandan, LI Yibo. Coordinated inertia response control for offshore low frequency wind power system based on adaptive virtual inertia of M3C [J]. Journal of Shandong University(Engineering Science), 2025, 55(5): 30-39.
[2] Jianqing WU,Yanqiang HUO,Jianzhu WANG,Hongyu GUO. Research review of highway differentiated toll collection [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 18-29.
[3] Hong YU,Juan DU,Lin WEI,Li ZHANG. Data fitting method for electricity consumption of power market users considering behavioral characteristics [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 113-119.
[4] Ying LI,Jiankun WANG. The classification of mild cognitive impairment based on supervised graph regularization and information fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 65-73.
[5] Caihui LIU,Qi ZHOU,Xiaowen YE. An intrusion detection model based on improved ReliefF algorithm [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 1-10.
[6] Chunhong CAO,Hongxuan DUAN,Ling CAO,Lele ZHANG,Kai HU,Fen XIAO. Real-time semantic segmentation of high-resolution remote sensing image based on multi-level feature cascade [J]. Journal of Shandong University(Engineering Science), 2021, 51(2): 19-25.
[7] ZHANG Qinyang, LI Xu, YAO Chunlong, LI Changwu. Aspect-level sentiment classification combined with syntactic dependency information [J]. Journal of Shandong University(Engineering Science), 2021, 51(2): 83-89.
[8] Zhuoyu XIAO,Pei HE,Guo CHEN,Yunbiao XU,Jie GUO. Design pattern classification mining with feature metrics constraints [J]. Journal of Shandong University(Engineering Science), 2020, 50(6): 48-58.
[9] HUO Bingqiang, ZHOU Tao, LU Huiling, DONG Yali, LIU Shan. Lung tumor benign-malignant classification based on multi-modal residual neural network and NRC algorithm [J]. Journal of Shandong University(Engineering Science), 2020, 50(6): 59-67.
[10] MA Changxia, ZHANG Chen. Pre-trained based joint model for intent classification and slot filling in Chinese spoken language understanding [J]. Journal of Shandong University(Engineering Science), 2020, 50(6): 68-75.
[11] ZHANG Feng, YANG Guixing, YUE Chenjing, HAO Quanrui, LI Dong. Determination and control method on power operating area of modular multilevel converter considering the constraint of internal dynamics [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 98-107.
[12] ZHAO Ningning, TANG Xuesong, ZHAO Mingbo. Depth segment classification algorithm based on convolutional neural network [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 22-27.
[13] Shiqi SONG,Yan PIAO,Zexin JIANG. Vehicle classification and tracking for complex scenes based on improved YOLOv3 [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 27-33.
[14] Chao FENG,Kunpeng XU,Lifei CHEN. LDA-based topic feature representation method for symbolic sequences [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 60-65.
[15] Chunyang LI,Nan LI,Tao FENG,Zhuhe WANG,Jingkai MA. Abnormal sound detection of washing machines based on deep learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 108-117.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] ZHANG Yong-hua,WANG An-ling,LIU Fu-ping . The reflected phase angle of low frequent inhomogeneous[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 22 -25 .
[2] KONG Xiang-zhen,LIU Yan-jun,WANG Yong,ZHAO Xiu-hua . Compensation and simulation for the deadband of the pneumatic proportional valve[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 99 -102 .
[3] LAI Xiang . The global domain of attraction for a kind of MKdV equations[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 87 -92 .
[4] YU Jia yuan1, TIAN Jin ting1, ZHU Qiang zhong2. Computational intelligence and its application in psychology[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 1 -5 .
[5] JI Tao,GAO Xu/sup>,SUN Tong-jing,XUE Yong-duan/sup>,XU Bing-yin/sup> . Characteristic analysis of fault generated traveling waves in 10 Kv automatic blocking and continuous power transmission lines[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 111 -116 .
[6] QIN Tong, SUN Fengrong*, WANG Limei, WANG Qinghao, LI Xincai. 3D surface reconstruction using the shape based interpolation guided by maximal discs[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(3): 1 -5 .
[7] SUN Dianzhu, ZHU Changzhi, LI Yanrui. [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 84 -86 .
[8] HU Tian-liang,LI Peng,ZHANG Cheng-rui,ZUO Yi . Design of a QEP decode counter based on VHDL[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(3): 10 -13 .
[9] CHEN Huaxin, CHEN Shuanfa, WANG Binggang. The aging behavior and mechanism of base asphalts[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(2): 125 -130 .
[10] BO De-Yun, ZHANG Dao-Jiang. Adaptive spectral clustering algorithm[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(5): 22 -26 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd