Improving Video Search and Retrieval Through Semantic Annotation

This paper affords a singular approach for enhancing video search and retrieval through the usage of semantic annotation. The proposed method includes levels of semantic annotation and semantic search and retrieval. Within the first level, semantic descriptors are mechanically generated from low-degree features of the video. Inside the 2 nd, those semantic descriptors are used to locate relevant films efficiently. Experiments are performed to evaluate the accuracy and performance of the proposed machine. Consequences indicate that the proposed gadget extensively outperforms existing techniques for video seek and retrieval, demonstrating the application of semantic annotation.