{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,26]],"date-time":"2024-08-26T11:49:03Z","timestamp":1724672943282},"reference-count":120,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T00:00:00Z","timestamp":1530835200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2019,1]]},"DOI":"10.1007\/s11042-018-6347-0","type":"journal-article","created":{"date-parts":[[2018,7,6]],"date-time":"2018-07-06T12:56:26Z","timestamp":1530881786000},"page":"2269-2309","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Explorations on visual localization from active to passive"],"prefix":"10.1007","volume":"78","author":[{"given":"Yongquan","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,7,6]]},"reference":[{"key":"6347_CR1","unstructured":"P Viola, M Jones (2001) Rapid object detection using a boosted cascade of simple features. CVPR"},{"key":"6347_CR2","unstructured":"N Dalal, B Triggs (2005) Histograms of Oriented Gradients for Human Detection. CVPR"},{"key":"6347_CR3","doi-asserted-by":"crossref","unstructured":"P Felzenszwalb, D Mcallester, D Ramanan (2008) A discriminatively trained, multiscale, deformable part modelfor. CVPR","DOI":"10.1109\/CVPR.2008.4587597"},{"key":"6347_CR4","doi-asserted-by":"crossref","unstructured":"Girshick R, Donahue J, Darrell T, et al (2014) Rich feature hierarchies for accurate object detection an semantic segmentation. CVPR","DOI":"10.1109\/CVPR.2014.81"},{"key":"6347_CR5","doi-asserted-by":"crossref","unstructured":"T-Y Lin, P Doll\u00e1r, R Girshick, K He, B Hariharan, S Belongie (2017) Feature pyramid networks for object detection. CVPR","DOI":"10.1109\/CVPR.2017.106"},{"key":"6347_CR6","doi-asserted-by":"crossref","unstructured":"R Girshick (2015) Fast R-CNN. ICCV","DOI":"10.1109\/ICCV.2015.169"},{"key":"6347_CR7","unstructured":"S Ren, K He, R Girshick, J Sun (2015) Faster R-CNN: Towards real-time object detection with region proposal networks. NIPS"},{"key":"6347_CR8","doi-asserted-by":"crossref","unstructured":"K He, G Gkioxari, P Doll\u00e1r, R Girshick (2017) Mask R-CNN. ICCV","DOI":"10.1109\/ICCV.2017.322"},{"key":"6347_CR9","doi-asserted-by":"crossref","unstructured":"J. Redmon, S. Divvala, R. Girshick, and A. Farhadi (2016) You only look once: Unified, real-time object detection. CVPR 1(2)","DOI":"10.1109\/CVPR.2016.91"},{"key":"6347_CR10","doi-asserted-by":"crossref","unstructured":"W Liu, D Anguelov, D Erhan, C Szegedy, S Reed (2016) SSD: Single shot multibox detector. ECCV","DOI":"10.1007\/978-3-319-46448-0_2"},{"issue":"2","key":"6347_CR11","first-page":"8","volume":"1","author":"J Redmon","year":"2017","unstructured":"Redmon J, Farhadi A (2017) YOLO9000: better, faster, stronger. CVPR 1(2):8","journal-title":"CVPR"},{"key":"6347_CR12","unstructured":"C-Y Fu, W Liu, A Ranga, A Tyagi, AC Berg (2016) DSSD:Deconvolutional single shot detector. arXiv:1701.06659"},{"key":"6347_CR13","unstructured":"A Krizhevsky, I Sutskever, GE Hinton (2012) ImageNet Classification with Deep Convolutional Neural Networks. Adv Neu Info Proc Syst (NIPS) 1097\u20131105"},{"key":"6347_CR14","doi-asserted-by":"crossref","unstructured":"J Deng, W Dong, R Socher, L-J Li, K Li, L Fei-Fei (2009) Imagenet: A large-scale hierarchical image database. Proc CVPR","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"6347_CR15","doi-asserted-by":"crossref","unstructured":"Y Jia, E Shelhamer, J Donahue, S Karayev, J Long, R Girshick, S Guadar-rama, T Darrell (2014) Caffe: Convolutional Architecture for Fast Feature Embedding. arXiv preprint arXiv:1408.5093","DOI":"10.1145\/2647868.2654889"},{"key":"6347_CR16","unstructured":"Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, Devin M, Ghemawat S, Irving G, Isard M, Kudlur M, Levenberg J, Monga R, Moore S, Murray DG, Steiner B, Tucker P, Vasudevan V, Warden P, Wicke M, Yu Y, Zheng X, Tensorflow (2016) A system for large-scale machine learning. Tech Rep Google Brain arXiv:1603.04467"},{"key":"6347_CR17","unstructured":"T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, Z Zhang (2015) MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. Neural Information Processing Systems. Workshop on Machine Learning Systems"},{"key":"6347_CR18","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1006\/jcss.1997.1504","volume":"55","author":"Y Freund","year":"1997","unstructured":"Freund Y, Schapire R (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 55:119\u2013139","journal-title":"J Comput Syst Sci"},{"key":"6347_CR19","doi-asserted-by":"crossref","unstructured":"T-Y Lin, P Goyal, R Girshick et al (2017) Focal Loss for Dense Object Detection, in ICCV","DOI":"10.1109\/ICCV.2017.324"},{"issue":"2","key":"6347_CR20","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/s11263-013-0620-5","volume":"104","author":"R Jasper","year":"2013","unstructured":"Jasper R, Uijlings R, van de Sande KEA, Gevers T et al (2013) Selective search for object recognition. Int J Comput Vis 104(2):154\u2013171","journal-title":"Int J Comput Vis"},{"key":"6347_CR21","doi-asserted-by":"crossref","unstructured":"A Shrivastava, A Gupta, R Girshick (2016) Training region-based object detectors with online hard example mining. CVPR","DOI":"10.1109\/CVPR.2016.89"},{"key":"6347_CR22","volume-title":"The elements of statistical learning","author":"T Hastie","year":"2008","unstructured":"Hastie T, Tibshirani R, Friedman J (2008) The elements of statistical learning. Springer series in statistics Springer, Berlin"},{"key":"6347_CR23","unstructured":"BD Lucas, T Kanade (1981) An iterative image registration technique with an application to stereo vision. IJCAI"},{"issue":"2","key":"6347_CR24","first-page":"12","volume":"2","author":"GR Bradski","year":"1998","unstructured":"Bradski GR (1998) Computer vision face tracking for use in a perceptual user interface. Intel Technol J 2(2):12\u201321","journal-title":"Intel Technol J"},{"issue":"5","key":"6347_CR25","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1109\/TPAMI.2003.1195991","volume":"25","author":"D Comaniciu","year":"2003","unstructured":"Comaniciu D, Ramesh V, Meer P (2003) Kernel-based object tracking. IEEE Trans Pattern Anal Mach Intell 25(5):564\u2013577","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6347_CR26","doi-asserted-by":"crossref","unstructured":"S Avidan (2004) Support Vector Tracking. IEEE Trans Patt Anal Mach Intel 1064\u20131072","DOI":"10.1109\/TPAMI.2004.53"},{"issue":"2","key":"6347_CR27","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1109\/TPAMI.2007.35","volume":"29","author":"S Avidan","year":"2007","unstructured":"Avidan S (2007) Ensemble tracking. IEEE Trans Pattern Anal Mach Intell 29(2):261\u2013271","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6347_CR28","doi-asserted-by":"crossref","unstructured":"Babenko B, Yang MH, Belongie S (2009) Visual tracking with online multiple instance learning, in CVPR","DOI":"10.1109\/CVPR.2009.5206737"},{"key":"6347_CR29","doi-asserted-by":"crossref","unstructured":"K Zhang, L Zhang, M-H Yang (2012) Real-Time compressive tracking, In ECCV","DOI":"10.1007\/978-3-642-33712-3_62"},{"issue":"7","key":"6347_CR30","doi-asserted-by":"publisher","first-page":"1409","DOI":"10.1109\/TPAMI.2011.239","volume":"34","author":"Z Kalal","year":"2012","unstructured":"Kalal Z, Mikolajczyk K, Matas J (2012) Tracking-learning-detection. TPAMI 34(7):1409\u20131422","journal-title":"TPAMI"},{"key":"6347_CR31","unstructured":"Zhong W, Lu H, Yang M-H (2012) Robust object tracking via sparse collaborative appearance model. CVPR"},{"key":"6347_CR32","doi-asserted-by":"crossref","unstructured":"Wen L, Cai Z, Lei Z (2014) Robustonline learned Spatio-Temporal Context model for visual tracking. IEEE Trans Image Proc","DOI":"10.1109\/TIP.2013.2293430"},{"key":"6347_CR33","first-page":"798","volume":"1","author":"A Adam","year":"2006","unstructured":"Adam A, Rivlin E, Shimshoni I (2006) Robust fragments based tracking using the integral histogram. CVPR 1:798\u2013805","journal-title":"CVPR"},{"key":"6347_CR34","doi-asserted-by":"crossref","unstructured":"Nebehay G, Pflugfelder R (2015) Clustering of static-adaptive correspondences for deformable object tracking. CVPR","DOI":"10.1109\/CVPR.2015.7298895"},{"key":"6347_CR35","doi-asserted-by":"crossref","unstructured":"Pernici F, Del Bimbo A (2014) Object tracking by oversampling local features. TPAMI 36(12)","DOI":"10.1109\/TPAMI.2013.250"},{"key":"6347_CR36","doi-asserted-by":"crossref","unstructured":"DS Bolme, JR Beveridge, BA Draper, YM Lui (2010) Visual object tracking using adaptive correlation filters. CVPR","DOI":"10.1109\/CVPR.2010.5539960"},{"key":"6347_CR37","unstructured":"J. F. Henriques, R. Caseiro, P. Martins, J. Batista, Exploiting the Circulant Structure of Tracking-by-detection with Kernels (2012) in ECCV. Springer Berlin Heidelberg 702\u2013715"},{"key":"6347_CR38","doi-asserted-by":"crossref","unstructured":"JF Henriques, R Caseiro, P Martins, J Batista (2014) High-speed tracking with kernelized correlation filters","DOI":"10.1109\/TPAMI.2014.2345390"},{"key":"6347_CR39","unstructured":"Y Li, J Zhu (2014) A scale adaptive kernel correlation filter tracker with feature integration, in Computer Vision-ECCV 2014 Workshops. Springer 254\u2013265"},{"key":"6347_CR40","doi-asserted-by":"crossref","unstructured":"M Danelljan, G H\u00e4ger, FS Khan, M Felsberg (2014) Accurate scale estimation for robust visual tracking, in Proceedings of the British Machine Vision Conference BMVC","DOI":"10.5244\/C.28.65"},{"key":"6347_CR41","unstructured":"M Danelljan, FS Khan, M Felsberg, and J vd Weijer (2014) Adaptive color attributes for real-time visual tracking, in Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. IEEE 1090\u20131097"},{"key":"6347_CR42","doi-asserted-by":"crossref","unstructured":"M Danelljan, FS Khan, M Felsberg (2015) Convolutional features for correlation filter based visual tracking. ICCV Workshops","DOI":"10.1109\/ICCVW.2015.84"},{"key":"6347_CR43","doi-asserted-by":"crossref","unstructured":"T Liu, G Wang, Q Yang (2015) Real-time part-based visual tracking via adaptive correlation filters. Proc IEEE Conf Comput Vis Patt Recog 4902\u20134912","DOI":"10.1109\/CVPR.2015.7299124"},{"key":"6347_CR44","doi-asserted-by":"crossref","unstructured":"C Ma, X Yang, C Zhang, M-H Yang (2015) Long-term correlation tracking. Proc IEEE Conf Comput Vis Patt Recog 5388\u20135396","DOI":"10.1109\/CVPR.2015.7299177"},{"key":"6347_CR45","doi-asserted-by":"crossref","unstructured":"M Danelljan, G Bhat, FS Khan, M Felsberg (2017) Eco: Efficient convolution operators for tracking. CVPR","DOI":"10.1109\/CVPR.2017.733"},{"issue":"6025","key":"6347_CR46","first-page":"68","volume":"53","author":"Z Chen","year":"2015","unstructured":"Chen Z, Hong Z, Tao D (2015) An experimental survey on correlation filter-based tracking. Comput Sci 53(6025):68\u201383","journal-title":"Comput Sci"},{"key":"6347_CR47","unstructured":"N Wang, D-Y Yeung (2013) Learning a deep compact image representation for visual tracking. Adv Neu Info Proc Syst 809\u2013817"},{"key":"6347_CR48","unstructured":"N Wang , S Li , A Gupta , DY Yeung (2015) Transferring Rich Feature Hierarchies for Robust Visual Tracking. Comput Sci"},{"key":"6347_CR49","doi-asserted-by":"crossref","unstructured":"Ma C, Huang JB, Yang X, Yang MH (2015) Hierarchical convolutional features for visual tracking. CVPR","DOI":"10.1109\/ICCV.2015.352"},{"key":"6347_CR50","doi-asserted-by":"crossref","unstructured":"Nam H, Han B (2016) Learning multi-domain convolutional neural networks for visual tracking. CVPR","DOI":"10.1109\/CVPR.2016.465"},{"key":"6347_CR51","unstructured":"L Bertinetto, J Valmadre, JF Henriques, A Vedaldi, PHS Torr (2016) Fully-convolutional Siamese networksfor object tracking. arXiv:1606.09549"},{"key":"6347_CR52","doi-asserted-by":"crossref","unstructured":"Held D, Thrun S, Savarese S (2016) Learning to track at 100 FPS with deep regression networks. ECCV","DOI":"10.1007\/978-3-319-46448-0_45"},{"key":"6347_CR53","doi-asserted-by":"crossref","unstructured":"C Harris, M Stephens (1988) A combined corner and edge detector. Proc AVC 147\u2013151","DOI":"10.5244\/C.2.23"},{"key":"6347_CR54","unstructured":"P Beaudet (1978) Rotationally invariant image operators. Proc IJCPR"},{"issue":"2","key":"6347_CR55","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1023\/A:1008045108935","volume":"30","author":"T Lindeberg","year":"1998","unstructured":"Lindeberg T (1998) Feature detection with automatic scale selection. IJCV 30(2):79\u2013116","journal-title":"IJCV"},{"key":"6347_CR56","doi-asserted-by":"crossref","unstructured":"D G Lowe (1999) Object recognition from local scale-invariant features. Proc CVPR 1150\u20131157","DOI":"10.1109\/ICCV.1999.790410"},{"key":"6347_CR57","doi-asserted-by":"crossref","unstructured":"H Bay, T Tuytelaars, LV Gool (2006) Surf: Speeded up robust features. Proc ECCV 404\u2013417","DOI":"10.1007\/11744023_32"},{"key":"6347_CR58","unstructured":"E Rosten T Drummond (2005) Fusing points and lines for high performance tracking. Proc ICCV 1508\u20131515"},{"key":"6347_CR59","doi-asserted-by":"crossref","unstructured":"E. Mair, G. D. Hager, D. Burschka, M. Suppa, and G. Hirzinger (2010) Adaptive and generic corner detection based on the accelerated segment test. Proc ECCV","DOI":"10.1007\/978-3-642-15552-9_14"},{"key":"6347_CR60","doi-asserted-by":"crossref","unstructured":"M Calonder, V Lepetit, C Strecha, P Fua (2010) Brief: Binary robust independent elementary features. Proc ECCV 778\u2013792","DOI":"10.1007\/978-3-642-15561-1_56"},{"key":"6347_CR61","doi-asserted-by":"crossref","unstructured":"E Rublee, V Rabaud, K Konolige, G Bradski (2011) Orb: An efficient alternative to sift or surf. Proc ICCV 2564\u20132571","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"6347_CR62","doi-asserted-by":"crossref","unstructured":"S Leutenegger, M Chli, R Siegwart (2011) Brisk: Binary robust invariant scalable keypoints. Proc ICCV 2548\u20132555","DOI":"10.1109\/ICCV.2011.6126542"},{"key":"6347_CR63","doi-asserted-by":"crossref","unstructured":"A Alahi, R Ortiz, P Vandergheynst (2012) Freak: Fast retina keypoint. Proc CVPR 510\u2013517","DOI":"10.1109\/CVPR.2012.6247715"},{"key":"6347_CR64","unstructured":"Y Uchida (2016) Local Feature Detectors, Descriptors, and Image Representations: A Survey, arXiv:1607.08368"},{"key":"6347_CR65","doi-asserted-by":"crossref","unstructured":"J Sivic, A Zisserman (2003) Video google: A text retrieval approach to object matching in videos. Proc ICCV1470\u20131477","DOI":"10.1109\/ICCV.2003.1238663"},{"key":"6347_CR66","doi-asserted-by":"crossref","unstructured":"D Nist\u00e9r, H Stew\u00e9nius (2006) Scalable recognition with a vocabulary tree. Proc CVPR 2161\u20132168","DOI":"10.1109\/CVPR.2006.264"},{"key":"6347_CR67","doi-asserted-by":"crossref","unstructured":"Y Jiang, C Ngo, J Yang (2007) Towards optimal bag-of-features for object categorization and semantic video retrieval. Proc CIVR 494\u2013501","DOI":"10.1145\/1282280.1282352"},{"key":"6347_CR68","doi-asserted-by":"crossref","unstructured":"H J\u00e9gou, M Douze, C Schmid (2008) Hamming embedding and weak geometric consistency for large scale image search. Proc ECCV 304\u2013317","DOI":"10.1007\/978-3-540-88682-2_24"},{"issue":"5","key":"6347_CR69","doi-asserted-by":"publisher","first-page":"1188","DOI":"10.1109\/TRO.2012.2197158","volume":"28","author":"D Galvez-Lopez","year":"2012","unstructured":"Galvez-Lopez D, Tardos JD (2012) Bags of binary words for fast place recognition in image sequences. IEEE Trans Robot 28(5):1188\u20131197","journal-title":"IEEE Trans Robot"},{"key":"6347_CR70","unstructured":"S Khan, D Wollherr (2015) Ibuild: Incremental bag of binary words for appearance based loop closure detection, in 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE 5441\u20135447"},{"key":"6347_CR71","unstructured":"L Han, L Fang (2017) Multi-Index Hashing for Loop closure Detection. Int Conf Multimed Expo"},{"key":"6347_CR72","doi-asserted-by":"crossref","unstructured":"L Han, L Fang (2017) Beyond SIFT Using Binary features in Loop Closure Detection. IROS","DOI":"10.1109\/IROS.2017.8206261"},{"key":"6347_CR73","doi-asserted-by":"crossref","unstructured":"K Chatfield, K Simonyan, A Vedaldi, A Zisserman (2014) Return of the Devil in the Details: Delving Deep into Convolutional Nets. Bri Mach Vis Conf (BMVC)","DOI":"10.5244\/C.28.6"},{"key":"6347_CR74","unstructured":"K Simonyan, A Zisserman (2014) Very Deep Convolutional Networks for Large-Scale Image Recognition. CoRR. URL \n                    http:\/\/arxiv.org\/abs\/1409.1556"},{"key":"6347_CR75","first-page":"584","volume":"8689","author":"A Babenko","year":"2014","unstructured":"Babenko A, Slesarev A, Chigorin A, Lempitsky V (2014) Neural codes for image retrieval. Eur Conf Comput Vis (ECCV) 8689:584\u2013599","journal-title":"Eur Conf Comput Vis (ECCV)"},{"key":"6347_CR76","doi-asserted-by":"publisher","unstructured":"Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D, Erhan D, Vanhoucke V, Rabinovich A (2015) Going deeper with convolutions. IEEE Conf Comput Vis Patt Recog (CVPR) 7\u201312. doi: \n                    https:\/\/doi.org\/10.1109\/CVPR.2015.7298594","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"6347_CR77","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. Comput Vis Pattern Recog. \n                    https:\/\/arxiv.org\/abs\/1512.03385","DOI":"10.1109\/CVPR.2016.90"},{"issue":"12","key":"6347_CR78","first-page":"2026","volume":"22","author":"X Zhang","year":"2015","unstructured":"Zhang X, Liu Z (2015) A survey on stereo vision matching algorithms. Intell Control Autom 22(12):2026\u20132031","journal-title":"Intell Control Autom"},{"key":"6347_CR79","first-page":"40","volume":"4","author":"D Kumari","year":"2016","unstructured":"Kumari D, Kaur K (2016) A survey on stereo matching techniques for 3D vision in image processing. Int J Eng Manuf 4:40\u201349","journal-title":"Int J Eng Manuf"},{"issue":"7","key":"6347_CR80","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1631\/jzus.CIDE1302","volume":"14","author":"YM Wei","year":"2013","unstructured":"Wei YM, Kang L, Yang B (2013) WU Ling-Da, applications of structure from motion: a survey. J Zhejiang Univ Sci C 14(7):486\u2013494","journal-title":"J Zhejiang Univ Sci C"},{"key":"6347_CR81","unstructured":"O Ozyesil, V Voroninski, R Basri (2017) A Singer, A Survey of Structure from Motion. Acta Numerica 26"},{"issue":"1","key":"6347_CR82","first-page":"363","volume":"184","author":"J Aulinas","year":"2008","unstructured":"Aulinas J, Petillot Y, Salvi J, Llad\u00f3 X (2008) The SLAM problem: a survey. Artif Intel Res Develop 184(1):363\u2013371","journal-title":"Artif Intel Res Develop"},{"key":"6347_CR83","unstructured":"Gouda W, Gomaa W, Ogawa T (2014) Vision based SLAM for humanoid robots: a survey, Japan-Egypt international conference on. Electronics:170\u2013175"},{"issue":"1","key":"6347_CR84","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1186\/s41074-017-0027-2","volume":"9","author":"T Taketomi","year":"2017","unstructured":"Taketomi T, Uchiyama H, Ikeda S (2017) Visual SLAM algorithms: a survey from 2010 to 2016. Ipsj Trans Comput Vis Appl 9(1):16","journal-title":"Ipsj Trans Comput Vis Appl"},{"key":"6347_CR85","unstructured":"Zhang X, Zhou X, Lin M, Sun J (2017) Shufflenet: An extremely efficient convolutional neural network for mobile devices. CVPR. arXiv preprint arXiv:1707.01083"},{"key":"6347_CR86","doi-asserted-by":"crossref","unstructured":"Luo JH, Wu J, and Lin W (2017) Thinet: A filter level pruning method for deep neural network compression. in ICCV","DOI":"10.1109\/ICCV.2017.541"},{"key":"6347_CR87","unstructured":"B Zhou, A Lapedriza, J Xiao, A Torralba, A Oliva (2014) Learning deep features for scene recognition using places database. Adv Neu Info Proc Syst"},{"key":"6347_CR88","unstructured":"B Zhou, A Lapedriza, A Khosla, A Oliva, A Torralba (2017) Places: A 10 million image database for scene recognition. IEEE Trans Pat Anal Mach Intel 99"},{"key":"6347_CR89","doi-asserted-by":"crossref","unstructured":"Kalal Z, Mikolajczyk K, Matas J (2010) Forward-backward error: automatic detection of tracking failures. In: Proceedings of the 2010 20th International Conference on Pattern Recognition. IEEE Comput Soc Washington 2756\u20132759","DOI":"10.1109\/ICPR.2010.675"},{"key":"6347_CR90","doi-asserted-by":"crossref","unstructured":"Kalal Z, Matas J, Mikolajczyk K (2010) P-N learning: bootstrapping binary classifiers by structural constraints. In: 23rd IEEE Conference on Computer Vision and Pattern Recognition, CVPR, San Francisco","DOI":"10.1109\/CVPR.2010.5540231"},{"key":"6347_CR91","doi-asserted-by":"crossref","unstructured":"J. Sanchez, F. Perronnin, T. Mensink, and J. Verbeek (2013) Image classification with the fisher vector: Theory and practice. Int\u2019l J Comput Vis","DOI":"10.1007\/s11263-013-0636-x"},{"key":"6347_CR92","unstructured":"C Doersch, A Gupta, AA Efros (2013) Mid-level visual element discovery as discriminative mode seeking. Adv Neu Info Proc Syst"},{"key":"6347_CR93","doi-asserted-by":"publisher","unstructured":"Nebehay G, Pflugfelder R (2014) Consensus-based matching and tracking of keypoints. TPAMI 27(10). doi: \n                    https:\/\/doi.org\/10.1109\/WACV.2014.6836013","DOI":"10.1109\/WACV.2014.6836013"},{"key":"6347_CR94","unstructured":"Y Yang, N Chen, S Jiang (2017) Collaborative strategy for visual object tracking. Multimed Tools Appl 1\u201321"},{"key":"6347_CR95","doi-asserted-by":"crossref","unstructured":"Vojir T, Matas J (2014) The enhanced flock of trackers. RRIV","DOI":"10.1007\/978-3-642-44907-9_6"},{"key":"6347_CR96","unstructured":"Kwon J, Lee KM (2009) Tracking of a non-rigid object via patch-based sampling. CVPR"},{"issue":"1","key":"6347_CR97","first-page":"772","volume":"6219","author":"DA Klein","year":"2010","unstructured":"Klein DA, Schulz D, Frintrop S, Cremers AB (2010) Adaptive real-time video-tracking for arbitrary objects. IEEE\/RSJ 6219(1):772\u2013777","journal-title":"IEEE\/RSJ"},{"key":"6347_CR98","doi-asserted-by":"crossref","unstructured":"Hare S, Saffari A, Torr PHS (2011) Struck: Structured output tracking with kernels. ICCV IEEE Int Conf 263\u2013270","DOI":"10.1109\/ICCV.2011.6126251"},{"key":"6347_CR99","doi-asserted-by":"crossref","unstructured":"Zhang K, Zhang L, Liu Q, Zhang D, Yang M-H (2014) Fast tracking via dense spatio-temporal context learning. ECCV","DOI":"10.1007\/978-3-319-10602-1_9"},{"key":"6347_CR100","doi-asserted-by":"crossref","unstructured":"M Jaderberg, A Vedaldi, A Zisserman (2014) Speeding up convolutional neural networks with low rank expansions. arXiv preprint arXiv:1405.3866","DOI":"10.5244\/C.28.88"},{"key":"6347_CR101","unstructured":"V Lebedev, Y Ganin, M Rakhuba, I Oseledets, V Lempitsky (2014) Speeding-up convolutional neural networks using fine-tuned cp-decomposition. arXiv preprint arXiv:1412.6553"},{"issue":"10","key":"6347_CR102","doi-asserted-by":"publisher","first-page":"1943","DOI":"10.1109\/TPAMI.2015.2502579","volume":"38","author":"X Zhang","year":"2016","unstructured":"Zhang X, Zou J, He K, Sun J (2016) Accelerating very deep convolutional networks for classification and detection. IEEE Trans Pattern Anal Mach Intell 38(10):1943\u20131955","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6347_CR103","unstructured":"W Wen, C Wu, Y Wang, Y Chen, H Li (2016) Learning structured sparsity in deep neural networks. Adv Neu Info Proc Syst 2074\u20132082"},{"key":"6347_CR104","doi-asserted-by":"crossref","unstructured":"M Rastegari, V Ordonez, J Redmon, A Farhadi (2016) Xnor-net: Imagenet classification using binary convolutional neural networks. Eur Conf Comput Vis 525\u2013542","DOI":"10.1007\/978-3-319-46493-0_32"},{"key":"6347_CR105","unstructured":"AG Howard (2017) Mobilenets: Efficient convolutional neural networks for mobile vision applications. forthcoming"},{"key":"6347_CR106","unstructured":"L Sifre (2014) Rigid-motion scattering for image classification, Ph. D. thesis"},{"key":"6347_CR107","first-page":"1023","volume":"2","author":"I Ulrich","year":"2000","unstructured":"Ulrich I, Nourbakhsh I (2000) Appearance-based place recognition for topological localization. ICRA 2:1023\u20131029","journal-title":"ICRA"},{"key":"6347_CR108","first-page":"748","volume":"6311","author":"J Knopp","year":"2010","unstructured":"Knopp J, Sivic J, Pajdla T (2010) Avoiding confusing features in place recognition. ECCV 6311:748\u2013761","journal-title":"ECCV"},{"issue":"1","key":"6347_CR109","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TRO.2015.2496823","volume":"32","author":"S Lowry","year":"2016","unstructured":"Lowry S, S\u00fcnderhauf N, Newman P, Leonard JJ, Cox D (2016) Visual place recognition: a survey. IEEE Trans Robots 32(1):1\u201319","journal-title":"IEEE Trans Robots"},{"issue":"9","key":"6347_CR110","doi-asserted-by":"publisher","first-page":"1699","DOI":"10.1109\/TPAMI.2011.41","volume":"33","author":"B Williams","year":"2011","unstructured":"Williams B, Klein G, Reid I (2011) Automatic re-localization and loop closing for real-time monocular slam. IEEE Trans Pattern Anal Mach Intell 33(9):1699\u20131712","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6347_CR111","unstructured":"H Strasdat (2012) Local accuracy and global consistency for efficient visual slam, Ph.D. thesis, Citeseer"},{"key":"6347_CR112","unstructured":"J Engel, T Sch\u00f6ps, D Cremers (2014) Lsd-slam: Large-scale direct monocular slam, in European Conference on Computer Vision. Springer 834\u2013849"},{"key":"6347_CR113","unstructured":"D Hahnel , W Burgard , D Fox , S Thrun (2003) An efficient fastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements. IROS"},{"key":"6347_CR114","doi-asserted-by":"crossref","unstructured":"JiaWang Bian, Wen-Yan Lin, Yasuyuki Matsushita, Sai-Kit Yeung, Tan Dat Nguyen, Ming-Ming Cheng (2017) GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence. Conf Comput Vis Patt Recog (CVPR)","DOI":"10.1109\/CVPR.2017.302"},{"issue":"14","key":"6347_CR115","doi-asserted-by":"publisher","first-page":"1611","DOI":"10.1177\/0278364913498910","volume":"32","author":"Y Latif","year":"2013","unstructured":"Latif Y, Cadena C, Neira J (2013) Robust loop closing over time for pose graph SLAM. Int J Robot Res 32(14):1611\u20131626","journal-title":"Int J Robot Res"},{"issue":"1","key":"6347_CR116","first-page":"I-652","volume":"1","author":"D Nister","year":"2004","unstructured":"Nister D, Naroditsky O, Bergen J (2004) Visual odometry. IEEE Comput Soc Conf Comput Vis Patt Recog 1(1):I-652\u2013I-659","journal-title":"IEEE Comput Soc Conf Comput Vis Patt Recog"},{"key":"6347_CR117","unstructured":"Y Hou, H Zhang, S Zhou (2015) Convolutional neuralnetwork-based image representation for visual loop closure detection, in information and automation, 2015 IEEE International Conference on. IEEE 2238\u20132245"},{"issue":"6","key":"6347_CR118","doi-asserted-by":"publisher","first-page":"647","DOI":"10.1177\/0278364908090961","volume":"27","author":"M Cummins","year":"2008","unstructured":"Cummins M, Newman P (2008) Fab-map: probabilistic localization and mapping in the space of appearance. Int J Robot Res 27(6):647\u2013665","journal-title":"Int J Robot Res"},{"issue":"3","key":"6347_CR119","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TRO.2013.2242375","volume":"29","author":"M Labbe","year":"2013","unstructured":"Labbe M, Michaud F (2013) Appearance-based loop closure detection for online large-scale and long-term operation. IEEE Trans Robot 29(3):734\u2013745","journal-title":"IEEE Trans Robot"},{"key":"6347_CR120","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/j.robot.2015.12.003","volume":"77","author":"N Kejriwal","year":"2016","unstructured":"Kejriwal N, Kumar S, Shibata T (2016) High performance loop closure detection using bag of word pairs. Robot Auton Syst 77:55\u201365","journal-title":"Robot Auton Syst"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-018-6347-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-6347-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-018-6347-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,7,5]],"date-time":"2019-07-05T19:24:08Z","timestamp":1562354648000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-018-6347-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,7,6]]},"references-count":120,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,1]]}},"alternative-id":["6347"],"URL":"https:\/\/doi.org\/10.1007\/s11042-018-6347-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,7,6]]},"assertion":[{"value":"22 December 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 May 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 June 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 July 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}