• DocumentCode
    730267
  • Title

    Face recognition for great apes: Identification of primates in videos

  • Author

    Loos, Alexander ; Kalyanasundaram, Talat Anand Mohan

  • Author_Institution
    Audio-Visual Syst., Fraunhofer Inst. for Digital Media Technol. IDMT, Ilmenau, Germany
  • fYear
    2015
  • fDate
    19-24 April 2015
  • Firstpage
    1548
  • Lastpage
    1552
  • Abstract
    Due to the ongoing biodiversity crisis, many species including great apes such as chimpanzees or gorillas are threatened and need to be protected. To overcome the catastrophic decline of biodiversity, biologists recently started to use remote cameras for wildlife monitoring. However, the manual analysis of the resulting image and video material is extremely tedious, time consuming, and highly cost intensive. To overcome the burden of time-consuming routine work we studied and proposed novel approaches for automatic chimpanzee identification in our previous work. Starting from the assumption that humans and our closest relatives share similar facial properties, algorithms for human face recognition were adapted and extended for this purpose. However, the proposed algorithms were designed to recognize chimpanzee individuals in still images only. In this paper we extend these ideas towards chimpanzee identification in video sequences. Thus, a novel frame weighting approach is presented which significantly improves the system´s accuracy.
  • Keywords
    biology computing; face recognition; video signal processing; automatic chimpanzee identification; biodiversity catastrophic decline; great apes; human face recognition; primates identification; remote camera; video sequence; wildlife monitoring; Accuracy; Face; Face detection; Face recognition; Training; Videos; Visualization; Animal Biometrics; Face Recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
  • Conference_Location
    South Brisbane, QLD
  • Type

    conf

  • DOI
    10.1109/ICASSP.2015.7178230
  • Filename
    7178230