{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,3]],"date-time":"2022-04-03T05:40:38Z","timestamp":1648964438548},"reference-count":8,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Artif. Intell. Tools"],"published-print":{"date-parts":[[1999,3]]},"abstract":"<jats:p> This paper presents a new method to estimate reflectance properties of non\u2013Lambertian surface by the least-mean-square (LMS) algorithm. In this paper, hybrid reflectance of an object is represented by the Torrance\u2013Sparrow model. We determine reflectance parameters which minimize the sum squared difference of the intensity distribution between the image of a sample sphere and the calculated image. The estimated reflectance parameters provide the range data with intensity distributions. Therefore, we generate three reference images of a range sphere, which has the same diameter as that of the sample, from the same viewpoint with different light directions. Direct matching of the object images to the references can precisely reconstruct the shape of the object. This paper uses a plate diffuse illumination to alleviate the effects of specular spike and highlights. The simulation results show that the proposed method can estimate reflectance properties of the hybrid surface, and also recover the object shape. <\/jats:p>","DOI":"10.1142\/s0218213099000026","type":"journal-article","created":{"date-parts":[[2003,4,22]],"date-time":"2003-04-22T11:42:22Z","timestamp":1051011742000},"page":"1-17","source":"Crossref","is-referenced-by-count":0,"title":["ESTIMATION OF HYBRID REFLECTANCE PROPERTIES AND SHAPE RECONSTRUCTION USING THE LMS METHOD"],"prefix":"10.1142","volume":"08","author":[{"given":"MAL-REY","family":"LEE","sequence":"first","affiliation":[{"name":"Dept. of Computer Science &amp; Eng. Chosun College Science &amp; Technology Chosun University, 290 Seosuk-Dong, Dongku, Kwang-Ju, 501-759, Korea"}]},{"given":"TAE-EUN","family":"KIM","sequence":"additional","affiliation":[{"name":"Dept of Multimedia, Nam Seoul University, 21, Maeju-ri, Seong hwan, Cheonahn-city, Choongnam, 330-800, Korea"}]}],"member":"219","published-online":{"date-parts":[[2011,11,21]]},"reference":[{"key":"p_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00128131"},{"key":"p_3","doi-asserted-by":"publisher","DOI":"10.1016\/0146-664X(82)90001-6"},{"key":"p_5","doi-asserted-by":"publisher","DOI":"10.1109\/34.85654"},{"key":"p_6","doi-asserted-by":"publisher","DOI":"10.1109\/70.54736"},{"key":"p_7","doi-asserted-by":"publisher","DOI":"10.1109\/34.491627"},{"key":"p_10","doi-asserted-by":"publisher","DOI":"10.1364\/JOSA.57.001105"},{"key":"p_12","doi-asserted-by":"publisher","DOI":"10.1109\/70.59367"},{"key":"p_13","doi-asserted-by":"publisher","DOI":"10.1109\/34.103274"}],"container-title":["International Journal on Artificial Intelligence Tools"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218213099000026","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T17:45:59Z","timestamp":1565199959000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218213099000026"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999,3]]},"references-count":8,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2011,11,21]]},"published-print":{"date-parts":[[1999,3]]}},"alternative-id":["10.1142\/S0218213099000026"],"URL":"https:\/\/doi.org\/10.1142\/s0218213099000026","relation":{},"ISSN":["0218-2130","1793-6349"],"issn-type":[{"value":"0218-2130","type":"print"},{"value":"1793-6349","type":"electronic"}],"subject":[],"published":{"date-parts":[[1999,3]]}}}