{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:27:19Z","timestamp":1760243239960,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2014,11,18]],"date-time":"2014-11-18T00:00:00Z","timestamp":1416268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Despite the prevalence of smart TVs, many consumers continue to use conventional TVs with supplementary set-top boxes (STBs) because of the high cost of smart TVs. However, because the processing power of a STB is quite low, the smart TV functionalities that can be implemented in a STB are very limited. Because of this, negligible research has been conducted regarding face recognition for conventional TVs with supplementary STBs, even though many such studies have been conducted with smart TVs. In terms of camera sensors, previous face recognition systems have used  high-resolution cameras, cameras with high magnification zoom lenses, or camera systems with panning and tilting devices that can be used for face recognition from various positions. However, these cameras and devices cannot be used in intelligent TV environments because of limitations related to size and cost, and only small, low cost  web-cameras can be used. The resulting face recognition performance is degraded because of the limited resolution and quality levels of the images. Therefore, we propose a new face recognition system for intelligent TVs in order to overcome the limitations associated with low resource set-top box and low cost web-cameras. We implement the face recognition system using a software algorithm that does not require special devices or cameras. Our research has the following four novelties: first, the candidate regions in a viewer\u2019s face are detected in an image captured by a camera connected to the STB via low processing background subtraction and face color filtering; second, the detected candidate regions of face are transmitted to a server that has high processing power in order to detect face regions accurately; third, in-plane rotations of the face regions are compensated based on similarities between the left and right half sub-regions of the face regions; fourth, various poses of the viewer\u2019s face region are identified using five templates obtained during the initial user registration stage and multi-level local binary pattern matching. Experimental results indicate that the recall; precision; and genuine acceptance rate were about 95.7%; 96.2%; and 90.2%, respectively.<\/jats:p>","DOI":"10.3390\/s141121726","type":"journal-article","created":{"date-parts":[[2014,11,18]],"date-time":"2014-11-18T11:39:36Z","timestamp":1416310776000},"page":"21726-21749","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Face Recognition System for Set-Top Box-Based Intelligent TV"],"prefix":"10.3390","volume":"14","author":[{"given":"Won","family":"Lee","sequence":"first","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Yeong","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Hyung","family":"Hong","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea"}]},{"given":"Kang","family":"Park","sequence":"additional","affiliation":[{"name":"Division of Electronics and Electrical Engineering, Dongguk University, 26 Pil-dong 3-ga, Jung-gu, Seoul 100-715, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2014,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/TCE.2003.1261192","article-title":"Development and Features of a TV Navigation System","volume":"49","author":"Isobe","year":"2003","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1109\/TCE.2005.1468026","article-title":"A Personalized TV Guide System Compliant with MHP","volume":"51","author":"Zhang","year":"2005","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1109\/TCE.2005.1405718","article-title":"Real-time Embedded Face Recognition for Smart Home","volume":"51","author":"Zuo","year":"2005","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2271","DOI":"10.1109\/TCE.2009.5373798","article-title":"Cognitive Face Analysis System for Future InteractiveTV","volume":"55","author":"An","year":"2009","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Lee, S.-H., Sohn, M.-K., Kim, D.-J., Kim, B., and Kim, H. (2012, January 26\u201328). Face Recognition of Near-infrared Images for Interactive Smart TV. Dunedin, New Zealand.","DOI":"10.1145\/2425836.2425902"},{"key":"ref_6","unstructured":"Lin, K.-H., Shiue, D.-H., Chiu, Y.-S., Tsai, W.-H., Jang, F.-J., and Chen, J.-S. (2012, January 2\u20135). Design and Implementation of Face Recognition-aided IPTV Adaptive Group Recommendation System Based on NLMS Algorithm. Gold Coast, Australia."},{"key":"ref_7","unstructured":"Lee, S.-H., Sohn, M.-K., Kim, D.-J., Kim, B., and Kim, H. (2013, January 11\u201314). Smart TV Interaction System Using Face and Hand Gesture Recognition. Las Vegas, NV, USA."},{"key":"ref_8","unstructured":"Logitech BCC950 Available online: http:\/\/www.logitech.com\/en-us\/support\/conferencecam?section=overview&crid=637&osid=14&bit=64."},{"key":"ref_9","unstructured":"Gonzalez, R.C., and Woods, R.E. (2002). Digital Image Processing, Prentice-Hall. [2nd ed.]."},{"key":"ref_10","unstructured":"Viola, P., and Jones, M. (2001, January 8\u201314). Rapid Object Detection Using a Boosted Cascade of Simple Features. Kauai, HI, USA."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","article-title":"Robust Real-time Face Detection","volume":"57","author":"Viola","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Chen, X., Rynn, P.J., and Bowyer, K.W. (2005, January 17\u201318). Fully Automated Facial Symmetry Axis Detection in Frontal Color Images. Buffalo, NY, USA.","DOI":"10.1109\/AUTOID.2005.29"},{"key":"ref_13","unstructured":"Phung, S.L., Bouzerdoum, A., and Chai, D. (2002, January 22\u201325). A Novel Skin Color Model in YCbCr Color Space and Its Application to Human Face Detection. Rochester, NY, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1016\/S0031-3203(00)00119-9","article-title":"A Novel Approach for Human Face Detection from Color Images under Complex Background","volume":"34","author":"Wang","year":"2001","journal-title":"Pattern Recognit."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1109\/TCE.2010.5606327","article-title":"Skin Color Enhancement Based on Favorite Skin Color in HSV Color Space","volume":"56","author":"Zhang","year":"2010","journal-title":"IEEE Trans. Consum. Electron."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1950","DOI":"10.1109\/TCYB.2014.2300175","article-title":"Data uncertainty in face recognition","volume":"44","author":"Xu","year":"2014","journal-title":"IEEE Trans. Cybern."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1109\/TPAMI.2007.1014","article-title":"Illumination invariant face recognition using near-infrared images","volume":"29","author":"Li","year":"2007","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1109\/TIFS.2014.2318433","article-title":"On recognizing faces in videos using clustering-based re-ranking and fusion","volume":"9","author":"Bhatt","year":"2014","journal-title":"IEEE Trans. Inf. Forensic Secur."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/0031-3203(95)00067-4","article-title":"A Comparative Study of Texture Measures with Classification Based on Feature Distributions","volume":"29","author":"Ojala","year":"1996","journal-title":"Pattern Recognit."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1109\/TPAMI.2002.1017623","article-title":"Multiresolution Gray-scale and Rotation Invariant Texture Classification with Local Binary Patterns","volume":"24","author":"Ojala","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1262","DOI":"10.1016\/j.patcog.2010.12.005","article-title":"Age Estimation Using a Hierarchical Classifier Based on Global and Local Facial Features","volume":"44","author":"Choi","year":"2011","journal-title":"Pattern Recognit."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Happy, S.L., Georage, A., and Routray, A. (2012, January 27\u201329). A Real Time Facial Expression Classification System Using Local Binary Patterns. Kharagpur, India.","DOI":"10.1109\/IHCI.2012.6481802"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ahonen, T., Hadid, A., and Pietik\u00e4inen, M. (2004, January 11\u201314). Face Recognition with Local Binary Patterns. Prague, Czech Republic.","DOI":"10.1007\/978-3-540-24670-1_36"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1109\/34.598228","article-title":"Eigenfaces vs. fisherfaces: Recognition using class specific linear projection","volume":"19","author":"Belhumeur","year":"1997","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1162\/jocn.1991.3.1.71","article-title":"Eigenfaces for recognition","volume":"3","author":"Turk","year":"1991","journal-title":"J. Cogn. Neurosci."},{"key":"ref_26","unstructured":"Li, S.Z., Hou, X.W., Zhang, H.J., and Cheng, Q.S. (2001, January 8\u201314). Learning Spatially Localized, Parts-based Representation. Kauai, HI, USA."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2871","DOI":"10.1016\/j.patcog.2010.03.008","article-title":"SVM-based feature extraction for face recognition","volume":"43","author":"Kim","year":"2010","journal-title":"Pattern Recognit."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Froba, B., and Ernst, A. (2004, January 17\u201319). Face Detection with the Modified Census Transform. Seoul, Korea.","DOI":"10.1109\/AFGR.2004.1301514"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/11\/21726\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:09:33Z","timestamp":1760216973000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/11\/21726"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,11,18]]},"references-count":28,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2014,11]]}},"alternative-id":["s141121726"],"URL":"https:\/\/doi.org\/10.3390\/s141121726","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2014,11,18]]}}}