{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T04:08:43Z","timestamp":1750910923705,"version":"3.41.0"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319677767"},{"type":"electronic","value":"9783319677774"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-67777-4_28","type":"book-chapter","created":{"date-parts":[[2017,9,13]],"date-time":"2017-09-13T15:24:34Z","timestamp":1505316274000},"page":"325-334","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Saliency Detection via Combining Global Shape and Local Cue Estimation"],"prefix":"10.1007","author":[{"given":"Qiang","family":"Qi","sequence":"first","affiliation":[]},{"given":"Muwei","family":"Jian","sequence":"additional","affiliation":[]},{"given":"Yilong","family":"Yin","sequence":"additional","affiliation":[]},{"given":"Junyu","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Wenyin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Yu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,14]]},"reference":[{"issue":"1","key":"28_CR1","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1109\/TSMCB.2009.2037923","volume":"41","author":"K Huang","year":"2010","unstructured":"Huang, K., et al.: Biologically inspired features for scene classification in video surveillance. IEEE Trans. Syst. Man Cybern. B Cybern. 41(1), 307\u2013313 (2010)","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern."},{"issue":"10","key":"28_CR2","doi-asserted-by":"publisher","first-page":"2002","DOI":"10.1109\/TPAMI.2014.2315808","volume":"36","author":"K Zhang","year":"2014","unstructured":"Zhang, K., Zhang, L., Yang, M.H.: Fast compressive tracking. IEEE Trans. PAMI 36(10), 2002\u20132015 (2014)","journal-title":"IEEE Trans. PAMI"},{"issue":"4","key":"28_CR3","first-page":"1779","volume":"25","author":"K Zhang","year":"2016","unstructured":"Zhang, K., Liu, Q., Wu, Y.: Robust visual tracking via convolutional networks without training. IEEE TIP 25(4), 1779\u20131792 (2016)","journal-title":"IEEE TIP"},{"issue":"4","key":"28_CR4","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1179\/136821910X12867873897355","volume":"59","author":"MW Jian","year":"2011","unstructured":"Jian, M.W., Dong, J.Y., Ma, J.: Image retrieval using wavelet-based salient regions. Imaging Sci. J. 59(4), 219\u2013231 (2011)","journal-title":"Imaging Sci. J."},{"issue":"6","key":"28_CR5","doi-asserted-by":"publisher","first-page":"2032","DOI":"10.1109\/TSMCB.2013.2238927","volume":"43","author":"G Zhu","year":"2013","unstructured":"Zhu, G., Wang, Q., Yuan, Y., Yan, P.: Learning saliency by MRF and differential threshold. IEEE Trans. Cybern. 43(6), 2032\u20132043 (2013)","journal-title":"IEEE Trans. Cybern."},{"doi-asserted-by":"crossref","unstructured":"Hsu, C.Y., Ding, J.J.: Efficient image segmentation algorithm using SLIC superpixels and boundary-focused region merging. In: Information, Communications and Signal Processing, pp. 1\u20135 (2013)","key":"28_CR6","DOI":"10.1109\/ICICS.2013.6782861"},{"issue":"11","key":"28_CR7","doi-asserted-by":"publisher","first-page":"1254","DOI":"10.1109\/34.730558","volume":"20","author":"L Itti","year":"1998","unstructured":"Itti, L., Koch, C., Niebur, E.: A model of saliency based visual attention for rapid scene analysis. IEEE Trans. PAMI 20(11), 1254\u20131259 (1998)","journal-title":"IEEE Trans. PAMI"},{"doi-asserted-by":"crossref","unstructured":"Harel, J., Koch, C., Perona, P.: Graph-based visual saliency. In: Advances in NIPS, pp. 545\u2013552 (2006)","key":"28_CR8","DOI":"10.7551\/mitpress\/7503.003.0073"},{"doi-asserted-by":"crossref","unstructured":"Ma, Y.F., Zhang, H.J.: Contrast-based image attention analysis by using fuzzy growing. In: ACM Conference on Multimedia, pp. 374\u2013381 (2003)","key":"28_CR9","DOI":"10.1145\/957013.957094"},{"doi-asserted-by":"crossref","unstructured":"Rahtu, E., Kannala, J., Salo, M., Heikkil\u00e4, J.: Segmenting salient objects from images and videos. In: Proceedings of 11th ECCV, pp. 366\u2013379 (2010)","key":"28_CR10","DOI":"10.1007\/978-3-642-15555-0_27"},{"issue":"10","key":"28_CR11","doi-asserted-by":"publisher","first-page":"1915","DOI":"10.1109\/TPAMI.2011.272","volume":"34","author":"S Goferman","year":"2012","unstructured":"Goferman, S., Zelnik-Manor, L., Tal, A.: Context-aware saliency detection. IEEE Trans. PAMI 34(10), 1915\u20131926 (2012)","journal-title":"IEEE Trans. PAMI"},{"issue":"1","key":"28_CR12","first-page":"55","volume":"22","author":"A Borji","year":"2013","unstructured":"Borji, A., Sihite, D.N., Itti, L.: Quantitative analysis of human-model agreement in visual saliency modeling: a comparative study. IEEE TIP 22(1), 55\u201369 (2013)","journal-title":"IEEE TIP"},{"issue":"4","key":"28_CR13","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1167\/13.4.11","volume":"13","author":"E Erdem","year":"2013","unstructured":"Erdem, E., Erdem, A.: Visual saliency estimation by nonlinearly integrating features using region covariances. J. Vis. 13(4), 11 (2013)","journal-title":"J. Vis."},{"issue":"7","key":"28_CR14","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/LSP.2013.2260737","volume":"20","author":"C Yang","year":"2013","unstructured":"Yang, C., Zhang, L., Lu, H.: Graph-regularized saliency detection with convex-hull-based center prior. IEEE Sig. Process. Lett. 20(7), 637\u2013640 (2013)","journal-title":"IEEE Sig. Process. Lett."},{"issue":"9","key":"28_CR15","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1109\/LSP.2014.2323407","volume":"21","author":"N Tong","year":"2014","unstructured":"Tong, N., Lu, H., Zhang, L., et al.: Saliency detection with multi-scale superpixels. IEEE Sig. Process. Lett. 21(9), 1035\u20131039 (2014)","journal-title":"IEEE Sig. Process. Lett."},{"issue":"3","key":"28_CR16","doi-asserted-by":"publisher","first-page":"569","DOI":"10.1109\/TPAMI.2014.2345401","volume":"37","author":"MM Cheng","year":"2015","unstructured":"Cheng, M.M., Mitra, N.J., Huang, X., et al.: Global contrast based salient region detection. IEEE Trans. PAMI 37(3), 569\u2013582 (2015)","journal-title":"IEEE Trans. PAMI"},{"doi-asserted-by":"crossref","unstructured":"Qin, Y., Lu, H., Xu, Y., et al.: Saliency detection via cellular automata. In: IEEE CVPR, pp. 110\u2013119 (2015)","key":"28_CR17","DOI":"10.1109\/CVPR.2015.7298606"},{"issue":"8","key":"28_CR18","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.J., Shen, L.L.: Visual-patch-attention-aware saliency detection. IEEE T. Cybernetics 45(8), 1575\u20131586 (2015)","journal-title":"IEEE T. Cybernetics"},{"doi-asserted-by":"crossref","unstructured":"Jian, M.M., Qi, Q., Sun, Y., Lam, K.M., et al: Saliency detection using quaternionic distance based weber descriptor and object cues. In: APSIPA ASC 2016, Korean (2016)","key":"28_CR19","DOI":"10.1109\/APSIPA.2016.7820767"},{"doi-asserted-by":"crossref","unstructured":"Zhang, D., Meng, D., Han, J.: Co-saliency detection via a self-paced multiple-instance learning framework. IEEE Trans. Pattern Anal. Mach. Intell. (2016)","key":"28_CR20","DOI":"10.1109\/ICCV.2015.75"},{"issue":"5","key":"28_CR21","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1109\/LSP.2017.2688136","volume":"24","author":"A Wang","year":"2017","unstructured":"Wang, A., Wang, M.: RGB-D salient object detection via minimum barrier distance transform and saliency fusion. IEEE Sig. Process. Lett. 24(5), 663\u2013667 (2017)","journal-title":"IEEE Sig. Process. Lett."},{"issue":"1","key":"28_CR22","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1109\/TIP.2016.2627804","volume":"26","author":"H Lu","year":"2017","unstructured":"Lu, H., Zhang, X., Qi, J., et al.: Co-Bootstrapping saliency. IEEE Trans. Image Process. 26(1), 414\u2013425 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"28_CR23","series-title":"Lecture Notes in Electrical Engineering","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/978-981-10-4154-9_18","volume-title":"Information Science and Applications 2017","author":"X Lin","year":"2017","unstructured":"Lin, X., Yan, Z., Jiang, L.: Saliency detection via foreground and background seeds. In: Kim, K., Joukov, N. (eds.) ICISA 2017. LNEE, vol. 424, pp. 145\u2013154. Springer, Singapore (2017). doi:10.1007\/978-981-10-4154-9_18"},{"doi-asserted-by":"crossref","unstructured":"Oliva, A., Torralba, A., Castelhano, M.S., et al.: Top-down control of visual attention in object detection. In: IEEE ICIP, vol. 1 (2003)","key":"28_CR24","DOI":"10.1109\/ICIP.2003.1246946"},{"doi-asserted-by":"crossref","unstructured":"Cholakkal, H., Rajan, D., Johnson, J.: Top-down saliency with locality-constrained contextual sparse coding. In: BMVC (2015)","key":"28_CR25","DOI":"10.5244\/C.29.159"},{"issue":"3","key":"28_CR26","doi-asserted-by":"publisher","first-page":"576","DOI":"10.1109\/TPAMI.2016.2547384","volume":"39","author":"J Yang","year":"2017","unstructured":"Yang, J., Yang, M.H.: Top-down visual saliency via joint CRF and dictionary learning. IEEE Trans. PAMI 39(3), 576\u2013588 (2017)","journal-title":"IEEE Trans. PAMI"},{"doi-asserted-by":"crossref","unstructured":"He, S., Lau, R.W.H., Yang, Q.: Exemplar-driven top-down saliency detection via deep association. In: IEEE CVPR, pp. 5723\u20135732 (2016)","key":"28_CR27","DOI":"10.1109\/CVPR.2016.617"},{"issue":"6","key":"28_CR28","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1007\/s00138-016-0754-x","volume":"27","author":"I Rahman","year":"2016","unstructured":"Rahman, I., Hollitt, C., Zhang, M.: Contextual-based top-down saliency feature weighting for target detection. Mach. Vis. Appl. 27(6), 893\u2013914 (2016)","journal-title":"Mach. Vis. Appl."},{"doi-asserted-by":"crossref","unstructured":"Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: IEEE CVPR, pp. 1597\u20131604 (2009)","key":"28_CR29","DOI":"10.1109\/CVPRW.2009.5206596"},{"doi-asserted-by":"crossref","unstructured":"Perazzi, F., Krahenbuhl, P., Pritch, Y., Hornung, A.: Saliency filters: contrast based filtering for salient region detection. In: IEEE CVPR, pp. 733\u2013740 (2012)","key":"28_CR30","DOI":"10.1109\/CVPR.2012.6247743"},{"unstructured":"Lan, R.S., Zhou, Y.C., Tang, Y.: Quaternionic weber local descriptor of color images. IEEE Trans. Circuits Syst. Video Technol. (2015)","key":"28_CR31"},{"issue":"10","key":"28_CR32","doi-asserted-by":"publisher","first-page":"3258","DOI":"10.1016\/j.patcog.2014.12.005","volume":"48","author":"N Tong","year":"2015","unstructured":"Tong, N., Lu, H., Zhang, Y., et al.: Salient object detection via global and local cues. Pattern Recogn. 48(10), 3258\u20133267 (2015)","journal-title":"Pattern Recogn."},{"doi-asserted-by":"crossref","unstructured":"Wang, J., Yang, J., Yu, K., Lv, F., Huang, T., Gong, Y.: Locality-constrained linear coding for image classification. In: IEEE CVPR, pp. 3360\u20133367 (2010)","key":"28_CR33","DOI":"10.1109\/CVPR.2010.5540018"},{"issue":"4","key":"28_CR34","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1007\/s00371-013-0867-4","volume":"30","author":"MM Cheng","year":"2014","unstructured":"Cheng, M.M., Mitra, N.J., Huang, X.: Salient shape: group saliency in image collections. Vis. Comput. 30(4), 443\u2013453 (2014)","journal-title":"Vis. Comput."},{"key":"28_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-017-5032-z","author":"M Jian","year":"2017","unstructured":"Jian, M., Qi, Q., et al.: Saliency detection using quaternionic distance based weber local descriptor and level priors. Multimedia Tools Appl. (2017). doi:10.1007\/s11042-017-5032-z","journal-title":"Multimedia Tools Appl."}],"container-title":["Lecture Notes in Computer Science","Intelligence Science and Big Data Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-67777-4_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T18:47:30Z","timestamp":1750877250000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-67777-4_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319677767","9783319677774"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-67777-4_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"14 September 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IScIDE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Science and Big Data Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dalian","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":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iscide2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ice.dlut.edu.cn\/IScIDE\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}