Content-based Video Retrieval Systems: A Review

Searching the useful videos rapidly and accurately is a tedious task if a user wants to search videos from the large repositories. Content-based retrieval is a better option than other text-based retrieval systems. These systems employ various techniques to analyze video content and enable efficient retrieval based on visual, audio, and textual features. This research study reviews the existing CBVR systems in literature, aims to provide a comprehensive overview of the methods, approaches, and performance evaluation parameters along with several sub process of video analysis used in different multimedia applications like recognition, segmentation, classification, motion detection etc., which can be useful in new CBVR system development. This research review covers a wide range of topics, including feature extraction, similarity measures, indexing methods, and user interface designs. Additionally, the paper highlights the challenges and future directions in CBVR research. The insights from this review can serve as a valuable resource for researchers, practitioners, and system developers working in the field of video retrieval.