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010   $a3-319-33796-3
024 7 $a10.1007/978-3-319-33796-8
035   $a(CKB)3710000000667227
035   $a(DE-He213)978-3-319-33796-8
035   $a(MiAaPQ)EBC4526867
035   $a(PPN)194074099
035   $a(EXLCZ)993710000000667227
100   $a20160511d2016      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aMultimodal Computational Attention for Scene Understanding and Robotics$b[electronic resource] /$fby Boris Schauerte
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (XXIV, 203 p. 55 illus., 51 illus. in color.) 
225 1 $aCognitive Systems Monographs,$x1867-4925 ;$v30
311   $a3-319-33794-7 
320   $aIncludes bibliographical references at the end of each chapters.
327   $aIntroduction -- Background -- Bottom-up Audio-Visual Attention for Scene Exploration -- Multimodal Attention with Top-Down Guidance -- Conclusion -- Applications -- Dataset Overview.
330   $aThis book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated. .
410  0$aCognitive Systems Monographs,$x1867-4925 ;$v30
606   $aComputational intelligence
606   $aRobotics
606   $aAutomation
606   $aArtificial intelligence
606   $aOptical data processing
606   $aPattern recognition
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021
606   $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X
615  0$aComputational intelligence.
615  0$aRobotics.
615  0$aAutomation.
615  0$aArtificial intelligence.
615  0$aOptical data processing.
615  0$aPattern recognition.
615 14$aComputational Intelligence.
615 24$aRobotics and Automation.
615 24$aArtificial Intelligence.
615 24$aImage Processing and Computer Vision.
615 24$aPattern Recognition.
676   $a629.892637
700   $aSchauerte$b Boris$4aut$4http://id.loc.gov/vocabulary/relators/aut$0763054
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910254221003321
996   $aMultimodal Computational Attention for Scene Understanding and Robotics$91547665
997   $aUNINA