A precise approach to tracking dim-small targets using spectral fingerprint features
A precise method for accurately tracking dim- small targets, based on spectral fingerprint is proposed where traditional full color tracking seems impossible. A fingerprint model is presented to adequately extract spectral features. By creating a multidimensional feature space and extending the limi...
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| Veröffentlicht in: | Frontiers of Computer Science 2012-10, Vol.6 (5), p.527-536 |
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| container_end_page | 536 |
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| container_issue | 5 |
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| container_title | Frontiers of Computer Science |
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| creator | SHENG, Hao LI, Chao OUYANG, Yuanxin XIONG, Zhang |
| description | A precise method for accurately tracking dim- small targets, based on spectral fingerprint is proposed where traditional full color tracking seems impossible. A fingerprint model is presented to adequately extract spectral features. By creating a multidimensional feature space and extending the limited RGB information to the hyperspectral information, the improved precise tracking model based on a nonparamet- ric kernel density estimator is built using the probability his- togram of spectral features. A layered particle filter algorithm for spectral tracking is presented to avoid the object jumping abruptly. Finally, experiments are conducted that show that the tracking algorithm with spectral fingerprint features is ac- curate, fast, and robust. It meets the needs of dim-small target tracking adequately. |
| doi_str_mv | 10.1007/s11704-012-1106-2 |
| format | Article |
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Comput. Sci</addtitle><addtitle>Frontiers of Computer Science in China</addtitle><description>A precise method for accurately tracking dim- small targets, based on spectral fingerprint is proposed where traditional full color tracking seems impossible. A fingerprint model is presented to adequately extract spectral features. By creating a multidimensional feature space and extending the limited RGB information to the hyperspectral information, the improved precise tracking model based on a nonparamet- ric kernel density estimator is built using the probability his- togram of spectral features. A layered particle filter algorithm for spectral tracking is presented to avoid the object jumping abruptly. Finally, experiments are conducted that show that the tracking algorithm with spectral fingerprint features is ac- curate, fast, and robust. It meets the needs of dim-small target tracking adequately.</description><subject>Algorithms</subject><subject>Computer Science</subject><subject>dim-small target</subject><subject>Fingerprints</subject><subject>LPF algorithm for spectral tracking</subject><subject>precise tracking</subject><subject>Research Article</subject><subject>spectral fingerprint features</subject><subject>Tracking</subject><subject>光谱信息</subject><subject>光谱特征</subject><subject>指纹特征</subject><subject>核密度估计</subject><subject>特征空间</subject><subject>粒子滤波算法</subject><subject>跟踪模型</subject><subject>跟踪算法</subject><issn>1673-7350</issn><issn>2095-2228</issn><issn>1673-7466</issn><issn>2095-2236</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kEtPwzAQhCMEEuXxA7gZcQ547cROjlXFS6rEpZwtJ1knKW2S2s6Bf4-jFLj15Idmdme-KLoD-giUyicHIGkSU2AxABUxO4sWICSPZSLE-e-dp_QyunJuS6lgTNBFtFmSwWLZOiR6GGyvy4b4nniry6-2q0nV7mO317sd8drW6B0Z3fTvBiyDaEdMeKEdbNt5YlD70aK7iS6M3jm8PZ7X0efL82b1Fq8_Xt9Xy3Vc8hx8nOUoc5FwQysUnCVGSg0hrikEr2ShaZakWEKR5qChYJXJTRZaZhRTXplC8uvoYZ4bgh9GdF5t-9F2YaViOWQSck5ZUMGsKm3vnEWjQtq9tt8KqJrgqRmeCvDUBE9NHjZ73NQsFPyffMqUzaamrRu0WAWyzilj-863aE9b748Zm76rD2HlX8iEi4xlQvAfI9uPOw</recordid><startdate>20121001</startdate><enddate>20121001</enddate><creator>SHENG, Hao</creator><creator>LI, Chao</creator><creator>OUYANG, Yuanxin</creator><creator>XIONG, Zhang</creator><general>Higher Education Press</general><general>SP Higher Education Press</general><general>Springer Nature B.V</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>20121001</creationdate><title>A precise approach to tracking dim-small targets using spectral fingerprint features</title><author>SHENG, Hao ; LI, Chao ; OUYANG, Yuanxin ; XIONG, Zhang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c391t-89e79643f0de6324f77a1466fb63d7ba0845ec1b591a1b2df9f817080e53dfb73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Algorithms</topic><topic>Computer Science</topic><topic>dim-small target</topic><topic>Fingerprints</topic><topic>LPF algorithm for spectral tracking</topic><topic>precise tracking</topic><topic>Research Article</topic><topic>spectral fingerprint features</topic><topic>Tracking</topic><topic>光谱信息</topic><topic>光谱特征</topic><topic>指纹特征</topic><topic>核密度估计</topic><topic>特征空间</topic><topic>粒子滤波算法</topic><topic>跟踪模型</topic><topic>跟踪算法</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>SHENG, Hao</creatorcontrib><creatorcontrib>LI, Chao</creatorcontrib><creatorcontrib>OUYANG, Yuanxin</creatorcontrib><creatorcontrib>XIONG, Zhang</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Frontiers of Computer Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>SHENG, Hao</au><au>LI, Chao</au><au>OUYANG, Yuanxin</au><au>XIONG, Zhang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A precise approach to tracking dim-small targets using spectral fingerprint features</atitle><jtitle>Frontiers of Computer Science</jtitle><stitle>Front Comput Sci</stitle><stitle>Front. Comput. Sci</stitle><addtitle>Frontiers of Computer Science in China</addtitle><date>2012-10-01</date><risdate>2012</risdate><volume>6</volume><issue>5</issue><spage>527</spage><epage>536</epage><pages>527-536</pages><issn>1673-7350</issn><issn>2095-2228</issn><eissn>1673-7466</eissn><eissn>2095-2236</eissn><abstract>A precise method for accurately tracking dim- small targets, based on spectral fingerprint is proposed where traditional full color tracking seems impossible. A fingerprint model is presented to adequately extract spectral features. By creating a multidimensional feature space and extending the limited RGB information to the hyperspectral information, the improved precise tracking model based on a nonparamet- ric kernel density estimator is built using the probability his- togram of spectral features. A layered particle filter algorithm for spectral tracking is presented to avoid the object jumping abruptly. 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| subjects | Algorithms Computer Science dim-small target Fingerprints LPF algorithm for spectral tracking precise tracking Research Article spectral fingerprint features Tracking 光谱信息 光谱特征 指纹特征 核密度估计 特征空间 粒子滤波算法 跟踪模型 跟踪算法 |
| title | A precise approach to tracking dim-small targets using spectral fingerprint features |
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