With the increasing omnipresence of video recording devices and the resulting abundance of digital video, finding a particular video sequence in ever-growing collections is more and more becoming a major challenge. Existing approaches to retrieve videos based on their content usually require prior knowledge about the origin and context of a particular video to work properly. Therefore, most state of the art video platforms still rely on text-based retrieval techniques to find desired sequences. In this paper, we present Cineast, a content-based video retrieval engine which retrieves video sequences based on their visual content. It supports Query-by-Example as well as Query-by-Sketch by using a multitude of low-level visual features in parallel. Cineast uses a collection of 200 videos from various genres with a combined length of nearly 20 h.
CITATION STYLE
Rossetto, L., Giangreco, I., Heller, S., Tănase, C., & Schuldt, H. (2016). Searching in video collections using sketches and sample images – the cineast system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9517, pp. 336–341). Springer Verlag. https://doi.org/10.1007/978-3-319-27674-8_30
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