SNOOPERTRACK: TEXT DETECTION AND TRACKING FOR OUTDOOR VIDEOS

Abstract : In this work we introduced SnooperTrack, an algorithm for the automatic detection and tracking of text objects -- such as store names, traffic signs, license plates, and advertisements -- in videos of outdoor scenes. The purpose is to improve the performances of text detection process in still images by taking advantage of the temporal coherence in videos. We first propose an efficient tracking algorithm using particle filtering framework with original region descriptors. The second contribution is our strategy to merge tracked regions and new detections. We also propose an improved version of our previously published text detection algorithm in still images. Tests indicate that SnooperTrack is fast, robust, enable false positive suppression, and achieved great performances in complex videos of outdoor scenes.
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https://hal.archives-ouvertes.fr/hal-00625414
Contributor : Rodrigo Minetto <>
Submitted on : Wednesday, September 21, 2011 - 3:40:10 PM
Last modification on : Thursday, March 21, 2019 - 1:07:56 PM

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Rodrigo Minetto, Nicolas Thome, Matthieu Cord, Neucimar J. Leite, Jorge Stolfi. SNOOPERTRACK: TEXT DETECTION AND TRACKING FOR OUTDOOR VIDEOS. IEEE International Conference on Image Processing (ICIP), Sep 2011, Brussels, Belgium. pp.505-508, ⟨10.1109/ICIP.2011.6116563⟩. ⟨hal-00625414⟩

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