Image coding based on maximum entropy partitioning for identifying improbable intensities related to facial expressions
In this paper we investigate information-theoretic image coding techniques that assign longer codes to improbable, imprecise and non-distinct intensities in the image. The variable length coding techniques when applied to cropped facial images of subjects with different facial expressions, highlight...
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| Published in | Sadhana (Bangalore) Vol. 41; no. 12; pp. 1393 - 1406 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New Delhi
Springer India
01.12.2016
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0256-2499 0973-7677 |
| DOI | 10.1007/s12046-016-0559-7 |
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| Abstract | In this paper we investigate information-theoretic image coding techniques that assign longer codes to improbable, imprecise and non-distinct intensities in the image. The variable length coding techniques when applied to cropped facial images of subjects with different facial expressions, highlight the set of low probability intensities that characterize the facial expression such as the creases in the forehead, the widening of the eyes and the opening and closing of the mouth. A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effective platform for future emotion categorization experiments. |
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| AbstractList | In this paper we investigate information-theoretic image coding techniques that assign longer codes to improbable, imprecise and non-distinct intensities in the image. The variable length coding techniques when applied to cropped facial images of subjects with different facial expressions, highlight the set of low probability intensities that characterize the facial expression such as the creases in the forehead, the widening of the eyes and the opening and closing of the mouth. A new coding scheme based on maximum entropy partitioning is proposed in our work, particularly to identify the improbable intensities related to different emotions. The improbable intensities when used as a mask decode the facial expression correctly, providing an effective platform for future emotion categorization experiments. |
| Author | Susan, Seba Chand, Shefali Aggarwal, Nandini Gupta, Ayush |
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| Cites_doi | 10.1109/26.380026 10.1109/TPAMI.2002.1017623 10.1147/sj.393.0705 10.1212/WNL.38.5.690 10.1063/1.3057290 10.1109/INDICON.2015.7443608 10.1109/AFGR.1998.670949 10.1016/j.cognition.2013.08.012 10.1023/B:VISI.0000013087.49260.fb 10.1109/LSP.2006.884012 10.1186/1471-2318-6-3 10.1016/j.cviu.2006.08.012 10.1145/632716.632878 10.1007/978-0-85729-997-0_19 10.1016/j.imavis.2008.08.005 10.1109/CVPRW.2003.10057 10.1109/CICN.2013.70 10.1097/00006842-197609000-00006 10.1109/ICMLC.2010.13 10.1007/s11760-013-0464-z 10.1016/j.neucom.2015.10.096 10.1016/j.neucom.2012.08.059 10.1007/978-1-4757-0450-1 10.1177/0022022180113003 10.7305/automatika.54-2.73 10.1145/634067.634250 10.1016/0165-1684(89)90090-X 10.1109/ISIT.2013.6620428 10.1109/CSNT.2014.104 10.1016/S0921-8890(02)00372-X 10.1002/j.1538-7305.1948.tb01338.x 10.1016/S0272-7358(02)00130-7 10.1109/JRPROC.1952.273898 10.1037/0012-1649.19.3.418 10.1109/ICCTICT.2016.7514583 10.1016/j.eswa.2006.01.025 10.1016/S0031-3203(99)00113-2 10.1109/34.531803 10.1109/TPAMI.2007.1110 10.1049/iet-ipr.2012.0527 10.1007/978-3-540-88693-8_37 10.1016/0304-3959(92)90213-U 10.1016/S1077-3142(03)00081-X |
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| Keywords | Variable length coding entropy coding Shannon–Fano coding maximum entropy partitioning Huffman coding facial expression recognition non-extensive entropy with Gaussian gain |
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| References_xml | – reference: Izard CarrollEChanges in facial expressions of 2-to 19-month-old infants following acute painDev. Psychol.198319341810.1037/0012-1649.19.3.418 – reference: ChandaBhabatoshMajumderDwijesh Dutta Digital image processing and analysis2004LtdPHI Learning Pvt – reference: SusanSebaHanmandluMadasuDifference tinvariant texture classificationIET Image Process.20137872573210.1049/iet-ipr.2012.0527 – reference: HuffmanDavid AA method for the construction of minimum redundancy codesProc. IRE19524091098110110.1109/JRPROC.1952.2738980137.13605 – reference: ManjunathBangalore SMaWei-YingTexture features for browsing and retrieval of image dataIEEE Trans. Pattern Anal. Mach. Intell.199618883784210.1109/34.531803 – reference: Seba Susan and Gitin Kakkar 2015 Decoding facial expressions using a new normalized similarity index. In 2015 Annual IEEE India Conference (INDICON), pp. 1–6. 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IEEE – reference: Prkachin KennethMThe consistency of facial expressions of pain: a comparison across modalitiesPain199251329730610.1016/0304-3959(92)90213-U – reference: Schwartz GaryEFairPaul LSaltPatriciaMandelMichel RKlermanGerald LFacial expression and imagery in depression: an electromyographic studyPsychosomatic Med.197638533734710.1097/00006842-197609000-00006 – reference: De la Torre Fernando and Jeffrey F Cohn 2011 Facial expression analysis. In: Visual analysis of humans, pp. 377–409. Springer London – reference: NagAmitavaBiswasSushantaSarkarDebasreeSarkarPartha PratimA novel technique for image steganography based on DWT and Huffman encodingInt. J. Comput. Sci. Security201146497610 – reference: SusanSebaHanmandluMadasuA non-extensive entropy feature and its application to texture classificationNeurocomputing201312021422510.1016/j.neucom.2012.08.059 – reference: MagalhãesFilipeCompressive sensing based face detection without explicit image reconstruction using support vector machines2013Berlin HeidelbergImage analysis and recognition. Springer758765 – reference: BezdekJCPattern recognition with fuzzy objective function algorithms1981New YorkPlenum Press10.1007/978-1-4757-0450-10503.68069 – reference: Jeon Byeung-woo, Jechang Jeong and Ju-ha Park 1996 Apparatus for variable-length coding and variable-length-decoding using a plurality of Huffman coding tables. U.S. Patent 5,528,628, issued June 18 – reference: ViolaPaulJonesMichael JRobust real-time face detectionInt. J. Comput. Vis.200457213715410.1023/B:VISI.0000013087.49260.fb – reference: HernándezBenjamínOlagueGustavoHammoudRiadTrujilloLeonardoRomeroEvaVisual learning of texture descriptors for facial expression recognition in thermal imageryComput. Vis. Image Understand.2007106225826910.1016/j.cviu.2006.08.012 – reference: FilkoDamirMartinovicGoranEmotion recognition system by a neural network based facial expression analysisAutomatika-J. Control Meas. Electron. Comput. Commun.201354226327210.7305/automatika.54-2.73 – reference: Kanade T, Cohn J F and Tian Y 2000 Comprehensive database for facial expression analysis. 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| SubjectTerms | Emotions Engineering Entropy Forehead Image coding Information theory Maximum entropy Partitioning Widening |
| Title | Image coding based on maximum entropy partitioning for identifying improbable intensities related to facial expressions |
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