Browsing by Keywords "Face detection"

Now showing items 1-6 of 6

    • Edge projections for eye localization 

      Turkan, M.; Pardas, M.; Cetin, A. E. (SPIE - International Society for Optical Engineering, 2008)
      An algorithm for human-eye localization in images is presented for faces with frontal pose and upright orientation. A given face region is filtered by a highpass wavelet-transform filter. In this way, edges of the region ...

    • Human eye localization using edge projections 

      Türkan, Mehmet; Pardas, M.; Çetin, Ahmet Enis (Institute for Systems and Technologies of Information, Control and Communication, 2007)
      In this paper, a human eye localization algorithm in images and video is presented for faces with frontal pose and upright orientation. A given face region is filtered by a high-pass filter of a wavelet transform. In this ...

    • Labeling of faces in personal photo albums 

      Şener, Emre; Yücel, Utku Can; Aksoy, Sercan; Büyükgebiz, ibrahim; Uzun, Burak; Duygulu, Pınar (IEEE, 2013)
      In this study, we propose a system for organizing personal photo collections. Motivated with the fact that people related queries are the most desired ones, we propose a method for labeling faces in photographs. After ...

    • Naming faces on the web 

      Zitouni, Hilal (Bilkent University, 2010)
      In this study, we introduce a method to name less-frequently appearing people on the web via naming frequently appearing ones first. Current image search engines are widely used for querying a person, however; retrievals ...

    • Recognizing faces in news photographs on the web 

      Zitouni H.; Bulut, M.F.; Duygulu P. (2009)
      We propose a graph based method in order to recognize the faces that appear on the web using a small training set. First, relevant pictures of the desired people are collected by querying the name in a text based search ...

    • Video copy detection using multiple visual cues and MPEG-7 descriptors 

      Küçüktunç, O.; Baştan M.; Güdükbay U.; Ulusoy, Ö. (Academic Press, 2010)
      We propose a video copy detection framework that detects copy segments by fusing the results of three different techniques: facial shot matching, activity subsequence matching, and non-facial shot matching using low-level ...