Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering
In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the result...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buchkapitel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 391 |
|---|---|
| container_issue | |
| container_start_page | 385 |
| container_title | |
| container_volume | 2191 |
| creator | Suppes, Alexander Suhling, Frank Hötter, Michael |
| description | In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the results of video data processing and robot motion data. Obstacle detection is realised by computing obstacle probability and subsequent application of a threshold operator. The first experiments show remarkably stable obstacle detection. |
| doi_str_mv | 10.1007/3-540-45404-7_51 |
| format | Book Chapter |
| fullrecord | <record><control><sourceid>proquest_pasca</sourceid><recordid>TN_cdi_pascalfrancis_primary_14047047</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EBC3061676_53_400</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2751-332b27d64491a76e76adee589bb8118e54373c867ea8d22280782349606c6a23</originalsourceid><addsrcrecordid>eNqNkElPwzAQhc0qqtI7R184ptger0fELpCQoJwtx52WQJqEOBz49zgUiSuWF9l-bzTvI-SEszlnzJxBoSQrZN5kYbziO2TmjIXx_rN2yYRrzgsA6fb-_oRymu2TCQMmCmckHJKJ4OBAcmWPyCylN5YHMKWlm5Cnp7b8TAN9LNMQYo30EgeMQ9U2dNW3G_o8YI9tim1XRXq3CWukz_jxiU3ERF9S1azpfag3oaHXVZ21-eGYHKxCnXD2e07J4vpqcXFbPDze3F2cPxRRGDX2LUphllpKx4PRaHRYIirrytJyblFJMBCtNhjsUghhmbEiZ9VMRx0ETMnptmwXUgz1qg9NrJLv-moT-i_PMwuTZ9bNt7rUjd1h78u2fU-eMz9y9uAzNv_D1I-cs0H-Fu7bnDQNHkdHxGboQx1fQ5dzJq-FBWeEl5p7yUYb_McGTHNttFeQXQy-ATU5itU</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>book_chapter</recordtype><pqid>EBC3061676_53_400</pqid></control><display><type>book_chapter</type><title>Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering</title><source>Springer Books</source><creator>Suppes, Alexander ; Suhling, Frank ; Hötter, Michael</creator><contributor>Florczyk, Stefan ; Radig, Bernd ; Florczyk, Stefan ; Radig, Bernd</contributor><creatorcontrib>Suppes, Alexander ; Suhling, Frank ; Hötter, Michael ; Florczyk, Stefan ; Radig, Bernd ; Florczyk, Stefan ; Radig, Bernd</creatorcontrib><description>In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the results of video data processing and robot motion data. Obstacle detection is realised by computing obstacle probability and subsequent application of a threshold operator. The first experiments show remarkably stable obstacle detection.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540425960</identifier><identifier>ISBN: 3540425969</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540454045</identifier><identifier>EISBN: 3540454047</identifier><identifier>DOI: 10.1007/3-540-45404-7_51</identifier><identifier>OCLC: 213934158</identifier><identifier>LCCallNum: TA1650 -- .D35 2001eb</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Computing: general ; Control theory. Systems ; Exact sciences and technology ; Image processing ; Kalman filter ; obstacle detection ; Pattern recognition ; Pattern recognition. Digital image processing. Computational geometry ; Robotics ; stereo based vision</subject><ispartof>Lecture notes in computer science, 2001, Vol.2191, p.385-391</ispartof><rights>Springer-Verlag Berlin Heidelberg 2001</rights><rights>2002 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2751-332b27d64491a76e76adee589bb8118e54373c867ea8d22280782349606c6a23</citedby><relation>Lecture Notes in Computer Science</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/3061676-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/3-540-45404-7_51$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/3-540-45404-7_51$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,775,776,780,785,786,789,4036,4037,27902,38232,41418,42487</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=14047047$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Florczyk, Stefan</contributor><contributor>Radig, Bernd</contributor><contributor>Florczyk, Stefan</contributor><contributor>Radig, Bernd</contributor><creatorcontrib>Suppes, Alexander</creatorcontrib><creatorcontrib>Suhling, Frank</creatorcontrib><creatorcontrib>Hötter, Michael</creatorcontrib><title>Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering</title><title>Lecture notes in computer science</title><description>In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the results of video data processing and robot motion data. Obstacle detection is realised by computing obstacle probability and subsequent application of a threshold operator. The first experiments show remarkably stable obstacle detection.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Computing: general</subject><subject>Control theory. Systems</subject><subject>Exact sciences and technology</subject><subject>Image processing</subject><subject>Kalman filter</subject><subject>obstacle detection</subject><subject>Pattern recognition</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Robotics</subject><subject>stereo based vision</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540425960</isbn><isbn>3540425969</isbn><isbn>9783540454045</isbn><isbn>3540454047</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2001</creationdate><recordtype>book_chapter</recordtype><recordid>eNqNkElPwzAQhc0qqtI7R184ptger0fELpCQoJwtx52WQJqEOBz49zgUiSuWF9l-bzTvI-SEszlnzJxBoSQrZN5kYbziO2TmjIXx_rN2yYRrzgsA6fb-_oRymu2TCQMmCmckHJKJ4OBAcmWPyCylN5YHMKWlm5Cnp7b8TAN9LNMQYo30EgeMQ9U2dNW3G_o8YI9tim1XRXq3CWukz_jxiU3ERF9S1azpfag3oaHXVZ21-eGYHKxCnXD2e07J4vpqcXFbPDze3F2cPxRRGDX2LUphllpKx4PRaHRYIirrytJyblFJMBCtNhjsUghhmbEiZ9VMRx0ETMnptmwXUgz1qg9NrJLv-moT-i_PMwuTZ9bNt7rUjd1h78u2fU-eMz9y9uAzNv_D1I-cs0H-Fu7bnDQNHkdHxGboQx1fQ5dzJq-FBWeEl5p7yUYb_McGTHNttFeQXQy-ATU5itU</recordid><startdate>2001</startdate><enddate>2001</enddate><creator>Suppes, Alexander</creator><creator>Suhling, Frank</creator><creator>Hötter, Michael</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>2001</creationdate><title>Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering</title><author>Suppes, Alexander ; Suhling, Frank ; Hötter, Michael</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2751-332b27d64491a76e76adee589bb8118e54373c867ea8d22280782349606c6a23</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2001</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Computing: general</topic><topic>Control theory. Systems</topic><topic>Exact sciences and technology</topic><topic>Image processing</topic><topic>Kalman filter</topic><topic>obstacle detection</topic><topic>Pattern recognition</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Robotics</topic><topic>stereo based vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Suppes, Alexander</creatorcontrib><creatorcontrib>Suhling, Frank</creatorcontrib><creatorcontrib>Hötter, Michael</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Suppes, Alexander</au><au>Suhling, Frank</au><au>Hötter, Michael</au><au>Florczyk, Stefan</au><au>Radig, Bernd</au><au>Florczyk, Stefan</au><au>Radig, Bernd</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering</atitle><btitle>Lecture notes in computer science</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>2001</date><risdate>2001</risdate><volume>2191</volume><spage>385</spage><epage>391</epage><pages>385-391</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540425960</isbn><isbn>3540425969</isbn><eisbn>9783540454045</eisbn><eisbn>3540454047</eisbn><abstract>In this paper a new approach for video based obstacle detection for a mobile robot is proposed, based on probabilistic evaluation of image data. Apart from the measurement data, also their uncertainties are taken into account. Evaluation is achieved using Kalman filter technique combining the results of video data processing and robot motion data. Obstacle detection is realised by computing obstacle probability and subsequent application of a threshold operator. The first experiments show remarkably stable obstacle detection.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/3-540-45404-7_51</doi><oclcid>213934158</oclcid><tpages>7</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2001, Vol.2191, p.385-391 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_14047047 |
| source | Springer Books |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Computing: general Control theory. Systems Exact sciences and technology Image processing Kalman filter obstacle detection Pattern recognition Pattern recognition. Digital image processing. Computational geometry Robotics stereo based vision |
| title | Robust Obstacle Detection from Stereoscopic Image Sequences Using Kalman Filtering |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T23%3A50%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pasca&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=bookitem&rft.atitle=Robust%20Obstacle%20Detection%20from%20Stereoscopic%20Image%20Sequences%20Using%20Kalman%20Filtering&rft.btitle=Lecture%20notes%20in%20computer%20science&rft.au=Suppes,%20Alexander&rft.date=2001&rft.volume=2191&rft.spage=385&rft.epage=391&rft.pages=385-391&rft.issn=0302-9743&rft.eissn=1611-3349&rft.isbn=9783540425960&rft.isbn_list=3540425969&rft_id=info:doi/10.1007/3-540-45404-7_51&rft_dat=%3Cproquest_pasca%3EEBC3061676_53_400%3C/proquest_pasca%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783540454045&rft.eisbn_list=3540454047&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=EBC3061676_53_400&rft_id=info:pmid/&rfr_iscdi=true |