In the context of his bachelor thesis, Alexander Theus developed a method for scene-text extraction in video called HyText, based on intermittent detection and bi-directional tracking. The method is able to match existing approaches in accuracy while being substantially faster. Alexander Theus, together with our colleagues Luca Rossetto (supervisor of the bachelor thesis) and Abraham Bernstein, has recently published a paper at the 28th International Conference on Multimedia Modeling (MMM 2022). Congratulations!

“HyText – A Scene-Text Extraction Method for Video Retrieval.“

Authors: Alexander Theus, Luca Rossetto, and Abraham Bernstein

Abstract: “Scene-text has been shown to be an effective query target for video retrieval applications in a known-item search context. While much progress has been made in scene-text extraction from individual pictures, the special case of video has so far received less attention. This paper introduces HyText, a scene-text extraction method for video with a focus on retrieval applications. HyText uses intermittent scene-text detection in combination with bi-directional tracking in order to increase throughput without reducing detection accuracy.”

You can read the full paper here.