Content-Based Video Indexing and Retrieval
IEEE MultiMedia
Time-Constrained Keyframe Selection Technique
Multimedia Tools and Applications
Statistical Shape Features for Content-Based Image Retrieval
Journal of Mathematical Imaging and Vision
Applications of Video-Content Analysis and Retrieval
IEEE MultiMedia
Evaluation of key frame-based retrieval techniques for video
Computer Vision and Image Understanding - Special isssue on video retrieval and summarization
A two-stage scheme for text detection in video images
Image and Vision Computing
Keyframe-Based Video Summary Using Visual Attention Clues
IEEE MultiMedia
VIRUS: video information retrieval using subtitles
Proceedings of the 14th International Academic MindTrek Conference: Envisioning Future Media Environments
MPEG-7 visual shape descriptors
IEEE Transactions on Circuits and Systems for Video Technology
A new key frame representation for video segment retrieval
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper, we present a framework for video retrieval using caption text and keyframe similarity. To extract caption text, we applied methods detecting and extracting image areas contain caption text and we used Tesseract-OCR engine to convert into plain text, then use Hunspell library for spell words. Next, we used Clucene search engine index and query on this text. We applied shape descriptors APR and ECM to descript keyframes of the video shots and use those descriptors as a feature vector of video shots. From the feature vectors were obtained, we used ANN library to index and search. The system which is built on the web-based application using ASP.NET support keyword-based and keyframe-based query. The results obtained from experiments produced very promising.