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Author (up) Dena Bazazian; Dimosthenis Karatzas; Andrew Bagdanov edit   pdf
  Title Soft-PHOC Descriptor for End-to-End Word Spotting in Egocentric Scene Images Type Conference Article
  Year 2018 Publication International Workshop on Egocentric Perception, Interaction and Computing at ECCV Abbreviated Journal  
  Volume Issue Pages  
  Abstract Word spotting in natural scene images has many applications in scene understanding and visual assistance. We propose Soft-PHOC, an intermediate representation of images based on character probability maps. Our representation extends the concept of the Pyramidal Histogram Of Characters (PHOC) by exploiting Fully Convolutional Networks to derive a pixel-wise mapping of the character distribution within candidate word regions. We show how to use our descriptors for word spotting tasks in egocentric camera streams through an efficient text line proposal algorithm. This is based on the Hough Transform over character attribute maps followed by scoring using Dynamic Time Warping (DTW). We evaluate our results on ICDAR 2015 Challenge 4 dataset of incidental scene text captured by an egocentric camera.  
  Address Munich; Alemanya; September 2018  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference ECCVW  
  Notes DAG; 600.129; 600.121; Approved no  
  Call Number Admin @ si @ BKB2018b Serial 3174  
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