{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T04:17:16Z","timestamp":1751948236067,"version":"3.41.2"},"publisher-location":"Cham","reference-count":30,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030007751"},{"type":"electronic","value":"9783030007768"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-00776-8_38","type":"book-chapter","created":{"date-parts":[[2018,9,18]],"date-time":"2018-09-18T08:14:58Z","timestamp":1537258498000},"page":"414-425","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Extracting Features of Interest from Small Deep Networks for Efficient Visual Tracking"],"prefix":"10.1007","author":[{"given":"Zhao","family":"Luo","sequence":"first","affiliation":[]},{"given":"Shiming","family":"Ge","sequence":"additional","affiliation":[]},{"given":"Yingying","family":"Hua","sequence":"additional","affiliation":[]},{"given":"Haolin","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Jin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,19]]},"reference":[{"key":"38_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1007\/978-3-319-48881-3_56","volume-title":"Computer Vision \u2013 ECCV 2016 Workshops","author":"L Bertinetto","year":"2016","unstructured":"Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H.S.: Fully-convolutional siamese networks for object tracking. In: Hua, G., J\u00e9gou, H. (eds.) ECCV 2016. LNCS, vol. 9914, pp. 850\u2013865. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-48881-3_56"},{"key":"38_CR2","doi-asserted-by":"crossref","unstructured":"Boddeti, V.N., Kanade, T., Kumar, B.V.K.V.: Correlation filters for object alignment. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 2291\u20132298 (2013)","DOI":"10.1109\/CVPR.2013.297"},{"key":"38_CR3","doi-asserted-by":"crossref","unstructured":"Bolme, D.S., Beveridge, J.R., Draper, B.A., Lui, Y.M.: Visual object tracking using adaptive correlation filters. In: IEEE Computer Vision and Pattern Recognition, pp. 2544\u20132550 (2010)","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"38_CR4","doi-asserted-by":"crossref","unstructured":"Danelljan, M., Hager, G., Khan, F.S., Felsberg, M.: Convolutional features for correlation filter based visual tracking. In: IEEE International Conference on Computer Vision Workshop, pp. 621\u2013629 (2015)","DOI":"10.1109\/ICCVW.2015.84"},{"key":"38_CR5","doi-asserted-by":"crossref","unstructured":"Danelljan, M., H\u00e4ger, G., Khan, F.S., Felsberg, M.: Accurate scale estimation for robust visual tracking. In: British Machine Vision Conference, pp. 65.1\u201365.11 (2014)","DOI":"10.5244\/C.28.65"},{"key":"38_CR6","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1007\/978-3-319-46454-1_29","volume-title":"Computer Vision \u2013 ECCV 2016","author":"M Danelljan","year":"2016","unstructured":"Danelljan, M., Robinson, A., Shahbaz Khan, F., Felsberg, M.: Beyond correlation filters: learning continuous convolution operators for visual tracking. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9909, pp. 472\u2013488. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46454-1_29"},{"issue":"9","key":"38_CR7","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb, P.F., Girshick, R., Mcallester, D., Ramanan, D.: Object detection with discriminatively trained part-based models. IEEE Trans. Pattern Anal. Mach. Intell. 32(9), 1627\u20131645 (2010)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"38_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1007\/978-3-319-46448-0_45","volume-title":"Computer Vision \u2013 ECCV 2016","author":"D Held","year":"2016","unstructured":"Held, D., Thrun, S., Savarese, S.: Learning to track at 100 FPS with deep regression networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9905, pp. 749\u2013765. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46448-0_45"},{"issue":"3","key":"38_CR9","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1109\/TPAMI.2014.2345390","volume":"37","author":"JF Henriques","year":"2015","unstructured":"Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. IEEE Trans. Pattern Anal. Mach. Intell. 37(3), 583\u2013596 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"38_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1007\/978-3-642-33765-9_50","volume-title":"Computer Vision \u2013 ECCV 2012","author":"JF Henriques","year":"2012","unstructured":"Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: Exploiting the circulant structure of tracking-by-detection with kernels. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7575, pp. 702\u2013715. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33765-9_50"},{"key":"38_CR11","doi-asserted-by":"crossref","unstructured":"Huang, C.M., Wang, S.C., Chang, C.F., Huang, C.I.: An air combat simulator in the virtual reality with the visual tracking system and force-feedback components. In: IEEE International Conference on Control Applications, vol. 1, pp. 515\u2013520 (2004)","DOI":"10.1109\/CCA.2004.1387263"},{"key":"38_CR12","unstructured":"Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: Squeezenet: Alexnet-level accuracy with 50x fewer parameters and $$<$$0.5MB model size (2016). arXiv: Computer Vision and Pattern Recognition"},{"issue":"8","key":"38_CR13","doi-asserted-by":"publisher","first-page":"1575","DOI":"10.1109\/TCYB.2014.2356200","volume":"45","author":"M Jian","year":"2015","unstructured":"Jian, M., Lam, K.M., Dong, J., Shen, L.: Visual-patch-attention-aware saliency detection. IEEE Trans. Cybern. 45(8), 1575\u20131586 (2015)","journal-title":"IEEE Trans. Cybern."},{"key":"38_CR14","doi-asserted-by":"crossref","unstructured":"Jian, M., Qi, Q., Dong, J., Sun, X., Sun, Y., Lam, K.: Saliency detection using quaternionic distance based weber local descriptor and level priors. Multimedia Tools and Applications, pp. 1\u201318 (2017)","DOI":"10.1109\/APSIPA.2016.7820767"},{"key":"38_CR15","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.jvcir.2018.03.008","volume":"53","author":"M Jian","year":"2018","unstructured":"Jian, M., Qi, Q., Dong, J., Yin, Y., Lam, K.M.: Integrating qdwd with pattern distinctness and local contrast for underwater saliency detection. J. Vis. Commun. Image Represent. 53, 31\u201341 (2018)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"38_CR16","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.E.: Imagenet classification with deep convolutional neural networks. In: International Conference on Neural Information Processing Systems, pp. 1097\u20131105 (2012)"},{"key":"38_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1007\/978-3-319-16181-5_18","volume-title":"Computer Vision - ECCV 2014 Workshops","author":"Y Li","year":"2015","unstructured":"Li, Y., Zhu, J.: A scale adaptive kernel correlation filter tracker with feature integration. In: Agapito, L., Bronstein, M.M., Rother, C. (eds.) ECCV 2014. LNCS, vol. 8926, pp. 254\u2013265. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-16181-5_18"},{"key":"38_CR18","doi-asserted-by":"crossref","unstructured":"Ma, C., Huang, J.B., Yang, X., Yang, M.H.: Hierarchical convolutional features for visual tracking. In: IEEE International Conference on Computer Vision, pp. 3074\u20133082 (2015)","DOI":"10.1109\/ICCV.2015.352"},{"key":"38_CR19","unstructured":"Matthias, M., Neil, S., Ghanem, B.: Context-aware correlation filter tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (2017)"},{"key":"38_CR20","doi-asserted-by":"crossref","unstructured":"Nam, H., Han, B.: Learning multi-domain convolutional neural networks for visual tracking. In: Computer Vision and Pattern Recognition, pp. 4293\u20134302 (2016)","DOI":"10.1109\/CVPR.2016.465"},{"issue":"1","key":"38_CR21","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1109\/70.210792","volume":"9","author":"NP Papanikolopoulos","year":"1993","unstructured":"Papanikolopoulos, N.P., Khosla, P.K., Kanade, T.: Visual tracking of a moving target by a camera mounted on a robot: a combination of control and vision. IEEE Trans. Robot. Autom. 9(1), 14\u201335 (1993)","journal-title":"IEEE Trans. Robot. Autom."},{"key":"38_CR22","doi-asserted-by":"crossref","unstructured":"Qi, Y., et al.: Hedged deep tracking. In: Computer Vision and Pattern Recognition, pp. 4303\u20134311 (2016)","DOI":"10.1109\/CVPR.2016.466"},{"key":"38_CR23","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: International Conference on Neural Information Processing Systems, pp. 91\u201399 (2015)"},{"issue":"3","key":"38_CR24","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M.S.: Imagenet large scale visual recognition challenge. Int. J. Comput. Vis. 115(3), 211\u2013252 (2015)","journal-title":"Int. J. Comput. Vis."},{"key":"38_CR25","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. Computer Science (2014)"},{"issue":"7","key":"38_CR26","doi-asserted-by":"publisher","first-page":"1442","DOI":"10.1109\/TPAMI.2013.230","volume":"36","author":"AWM Smeulders","year":"2014","unstructured":"Smeulders, A.W.M., Chu, D.M., Cucchiara, R., Calderara, S., Dehghan, A., Shah, M.: Visual tracking: an experimental survey. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1442\u20131468 (2014)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"38_CR27","doi-asserted-by":"crossref","unstructured":"Song, Y., Ma, C., Gong, L., Zhang, J., Lau, R.W.H., Yang, M.H.: Crest: convolutional residual learning for visual tracking. In: IEEE International Conference on Computer Vision, pp. 2574\u20132583 (2017)","DOI":"10.1109\/ICCV.2017.279"},{"key":"38_CR28","doi-asserted-by":"crossref","unstructured":"Valmadre, J., Bertinetto, L., Henriques, J.F., Vedaldi, A., Torr, P.H.S.: End-to-end representation learning for correlation filter based tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (2017)","DOI":"10.1109\/CVPR.2017.531"},{"issue":"9","key":"38_CR29","doi-asserted-by":"publisher","first-page":"1834","DOI":"10.1109\/TPAMI.2014.2388226","volume":"37","author":"Y Wu","year":"2015","unstructured":"Wu, Y., Lim, J., Yang, M.H.: Object tracking benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1834\u20131848 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"38_CR30","doi-asserted-by":"crossref","unstructured":"Wu, Y., Lim, J., Yang, M.H.: Online object tracking: A benchmark. In: IEEE Computer Vision and Pattern Recognition, pp. 2411\u20132418 (2013)","DOI":"10.1109\/CVPR.2013.312"}],"container-title":["Lecture Notes in Computer Science","Advances in Multimedia Information Processing \u2013 PCM 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00776-8_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T18:29:30Z","timestamp":1751912970000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00776-8_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030007751","9783030007768"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00776-8_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"19 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PCM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pacific Rim Conference on Multimedia","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hefei","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"pcm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/pcm2018.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}