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Author | Dena Bazazian; Dimosthenis Karatzas; Andrew Bagdanov | ||||
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 | |
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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 | ||||
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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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