{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T12:55:58Z","timestamp":1760705758173,"version":"3.37.3"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T00:00:00Z","timestamp":1622678400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T00:00:00Z","timestamp":1622678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,7]]},"DOI":"10.1007\/s11042-021-10910-3","type":"journal-article","created":{"date-parts":[[2021,6,3]],"date-time":"2021-06-03T20:03:23Z","timestamp":1622750603000},"page":"28329-28347","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A framework for continuous fingerspelling spotting for H.264\/AVC compressed videos using spatio-temporal Markov random field"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8547-4595","authenticated-orcid":false,"given":"Anjan Kumar","family":"Talukdar","sequence":"first","affiliation":[]},{"given":"M.K.","family":"Bhuyan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,6,3]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Abdari A, Amirjan P, Mansouri A (2019) Action recognition in compressed domain using residual information. In: 2019 4Th international conference on pattern recognition and image analysis (IPRIA). IEEE, pp 130\u2013134","key":"10910_CR1","DOI":"10.1109\/PRIA.2019.8785055"},{"doi-asserted-by":"crossref","unstructured":"Aly W, Aly S, Almotairi S (2019) User-independent american sign language alphabet recognition based on depth image and pcanet features. IEEE Access 7:123138\u2013123150","key":"10910_CR2","DOI":"10.1109\/ACCESS.2019.2938829"},{"issue":"1","key":"10910_CR3","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1109\/TMM.2018.2856094","volume":"21","author":"D Avola","year":"2019","unstructured":"Avola D, Bernardi M, Cinque L, Foresti GL, Massaroni C (2019) Exploiting recurrent neural networks and leap motion controller for the recognition of sign language and semaphoric hand gestures. IEEE Trans Multimed 21(1):234\u2013245","journal-title":"IEEE Trans Multimed"},{"issue":"2","key":"10910_CR4","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1111\/j.2517-6161.1974.tb00999.x","volume":"36","author":"J Besag","year":"1974","unstructured":"Besag J (1974) Spatial interaction and the statistical analysis of lattice systems. J R Stat Soc Ser B (Methodol) 36(2):192\u2013225","journal-title":"J R Stat Soc Ser B (Methodol)"},{"issue":"3","key":"10910_CR5","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1111\/j.2517-6161.1986.tb01412.x","volume":"48","author":"J Besag","year":"1986","unstructured":"Besag J (1986) On the statistical analysis of dirty pictures. J R Stat Soc Ser B (Methodol) 48(3):259\u2013279","journal-title":"J R Stat Soc Ser B (Methodol)"},{"issue":"3","key":"10910_CR6","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1109\/TMM.2011.2127464","volume":"13","author":"YM Chen","year":"2011","unstructured":"Chen YM, Bajic IV, Saeedi P (2011) Moving region segmentation from compressed video using global motion estimation and markov random fields. IEEE Trans Multimed 13(3):421\u2013431","journal-title":"IEEE Trans Multimed"},{"doi-asserted-by":"crossref","unstructured":"Chon J, Cherniavsky N, Riskin EA, Ladner RE (2009) Enabling access through real-time sign language communication over cell phones. In: 2009 Conference record of the forty-third asilomar conference on signals, systems and computers. IEEE, pp 588\u2013592","key":"10910_CR7","DOI":"10.1109\/ACSSC.2009.5469901"},{"doi-asserted-by":"crossref","unstructured":"Chon J, Whittle S, Riskin EA, Ladner RE (2011) Improving compressed video sign language conversations in the presence of data loss. In: 2011 Data compression conference. IEEE, pp 383\u2013392","key":"10910_CR8","DOI":"10.1109\/DCC.2011.45"},{"doi-asserted-by":"crossref","unstructured":"Chuan CH, Regina E, Guardino C (2014) American sign language recognition using leap motion sensor. In: 2014 13Th international conference on machine learning and applications. IEEE, pp 541\u2013544","key":"10910_CR9","DOI":"10.1109\/ICMLA.2014.110"},{"issue":"11","key":"10910_CR10","doi-asserted-by":"publisher","first-page":"3014","DOI":"10.1109\/TIP.2011.2132730","volume":"20","author":"FM Ciaramello","year":"2011","unstructured":"Ciaramello FM, Hemami SS (2011) A computational intelligibility model for assessment and compression of american sign language video. IEEE Trans Image Process 20(11):3014\u20133027","journal-title":"IEEE Trans Image Process"},{"doi-asserted-by":"crossref","unstructured":"Jalal MA, Chen R, Moore RK, Mihaylova L (2018) American sign language posture understanding with deep neural networks. In: 2018 21St international conference on information fusion (FUSION). IEEE, pp 573\u2013579","key":"10910_CR11","DOI":"10.23919\/ICIF.2018.8455725"},{"key":"10910_CR12","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.cviu.2015.08.001","volume":"141","author":"L Kane","year":"2015","unstructured":"Kane L, Khanna P (2015) A framework for live and cross platform fingerspelling recognition using modified shape matrix variants on depth silhouettes. Comput Vis Image Underst 141:138\u2013151","journal-title":"Comput Vis Image Underst"},{"doi-asserted-by":"crossref","unstructured":"Kang B, Tripathi S, Nguyen TQ (2015) Real-time sign language fingerspelling recognition using convolutional neural networks from depth map. In: 2015 3Rd IAPR asian conference on pattern recognition (ACPR). IEEE, pp 136\u2013140","key":"10910_CR13","DOI":"10.1109\/ACPR.2015.7486481"},{"unstructured":"Kayaalp IB (2003) Video segmentation using partially decoded mpeg bitstream. Ph.D. thesis METU","key":"10910_CR14"},{"issue":"1","key":"10910_CR15","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1109\/TIP.2012.2214049","volume":"22","author":"SH Khatoonabadi","year":"2013","unstructured":"Khatoonabadi SH, Bajic IV (2013) Video object tracking in the compressed domain using spatio-temporal markov random fields. IEEE Trans Image Process 22(1):300\u2013313","journal-title":"IEEE Trans Image Process"},{"unstructured":"Kim J, Chang HS, Kim J, Kim HM (2000) Efficient camera motion characterization for mpeg video indexing. In: 2000 IEEE International conference on multimedia and expo. ICME2000. Proceedings. Latest advances in the fast changing world of multimedia (cat. no. 00TH8532), vol 2. IEEE, pp 1171\u20131174","key":"10910_CR16"},{"doi-asserted-by":"crossref","unstructured":"Kim T, Shakhnarovich G, Livescu K (2013) Fingerspelling recognition with semi-markov conditional random fields. In: Proceedings of the IEEE International Conference on Computer Vision, pp 1521\u20131528","key":"10910_CR17","DOI":"10.1109\/ICCV.2013.192"},{"unstructured":"Lee J, Lee H, Lee D, Oh SJ (2017) A compressed-domain corner detection method for a dct-based compressed image. In: 2017 IEEE International conference on consumer electronics (ICCE). IEEE, pp 306\u2013307","key":"10910_CR18"},{"unstructured":"Li SZ (2009) Markov random field modeling in image analysis. Springer Science & Business Media","key":"10910_CR19"},{"doi-asserted-by":"crossref","unstructured":"Nguyen HB, Do HN (2019) Deep learning for american sign language fingerspelling recognition system. In: 2019 26Th international conference on telecommunications (ICT). IEEE, pp 314\u2013318","key":"10910_CR20","DOI":"10.1109\/ICT.2019.8798856"},{"doi-asserted-by":"crossref","unstructured":"Papadimitriou K, Potamianos G (2019) Fingerspelled alphabet sign recognition in upper-body videos. In: 2019 27Th european signal processing conference (EUSIPCO). IEEE, pp 1\u20135","key":"10910_CR21","DOI":"10.23919\/EUSIPCO.2019.8902541"},{"doi-asserted-by":"crossref","unstructured":"Ricco S, Tomasi C (2009) Fingerspelling recognition through classification of letter-to-letter transitions. In: Asian conference on computer vision. Springer, pp 214\u2013225","key":"10910_CR22","DOI":"10.1007\/978-3-642-12297-2_21"},{"doi-asserted-by":"crossref","unstructured":"Shi B, Del Rio AM, Keane J, Michaux J, Brentari D, Shakhnarovich G, Livescu K (2018) American sign language fingerspelling recognition in the wild. In: 2018 IEEE Spoken language technology workshop (SLT). IEEE, pp 145\u2013152","key":"10910_CR23","DOI":"10.1109\/SLT.2018.8639639"},{"doi-asserted-by":"crossref","unstructured":"Talukdar AK, Bhuyan M (2018) Movement epenthesis detection in continuous fingerspelling from a coarsely sampled motion vector field in h. 264\/avc video. In: 2018 IEEE Recent advances in intelligent computational systems (RAICS). IEEE, pp 26\u201330","key":"10910_CR24","DOI":"10.1109\/RAICS.2018.8634902"},{"doi-asserted-by":"crossref","unstructured":"Tazhigaliyeva N, Kalidolda N, Imashev A, Islam S, Aitpayev K, Parisi GI, Sandygulova A (2017) Cyrillic manual alphabet recognition in rgb and rgb-d data for sign language interpreting robotic system (slirs). In: 2017 IEEE International conference on robotics and automation (ICRA). IEEE, pp 4531\u20134536","key":"10910_CR25","DOI":"10.1109\/ICRA.2017.7989526"},{"issue":"8","key":"10910_CR26","doi-asserted-by":"publisher","first-page":"2858","DOI":"10.1016\/j.patcog.2010.03.007","volume":"43","author":"HD Yang","year":"2010","unstructured":"Yang HD, Lee SW (2010) Simultaneous spotting of signs and fingerspellings based on hierarchical conditional random fields and boostmap embeddings. Pattern Recogn 43(8):2858\u20132870","journal-title":"Pattern Recogn"},{"issue":"7","key":"10910_CR27","doi-asserted-by":"publisher","first-page":"1264","DOI":"10.1109\/TPAMI.2008.172","volume":"31","author":"HD Yang","year":"2009","unstructured":"Yang HD, Sclaroff S, Lee SW (2009) Sign language spotting with a threshold model based on conditional random fields. IEEE Trans Pattern Anal Mach Intell 31(7):1264\u20131277","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"doi-asserted-by":"crossref","unstructured":"Yang R, Sarkar S, Loeding B (2007) Enhanced level building algorithm for the movement epenthesis problem in sign language recognition. In: 2007 IEEE Conference on computer vision and pattern recognition. IEEE, pp 1\u20138","key":"10910_CR28","DOI":"10.1109\/CVPR.2007.383347"},{"issue":"3","key":"10910_CR29","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1109\/TPAMI.2009.26","volume":"32","author":"R Yang","year":"2010","unstructured":"Yang R, Sarkar S, Loeding B (2010) Handling movement epenthesis and hand segmentation ambiguities in continuous sign language recognition using nested dynamic programming. IEEE Trans Pattern Anal Mach Intell 32(3):462\u2013477","journal-title":"IEEE Trans Pattern Anal Mach Intell"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10910-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-10910-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10910-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T05:24:13Z","timestamp":1725168253000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-10910-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,3]]},"references-count":29,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2021,7]]}},"alternative-id":["10910"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-10910-3","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2021,6,3]]},"assertion":[{"value":"1 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 November 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 June 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}