Content based video retrieval via object based approach

One of the promising new directions for Content Based Video Retrieval is object based retrieval which allows the user to manipulate video object as a part of searching and browsing. The major obstacle for the use of objects in video retrieval is the appropriate representation of objects in video database. The purpose of this work is to present an object based framework consisting of entire processing chain needed to segment, represent and retrieve video object via appropriate content extraction. Such an object based approach can reduce the semantic gap to an acceptable level and provide satisfactory results in terms of performance metrics like Precision, Recall, Specificity, Sensitivity and Error rate. With this aim, Histogram of Fourier Coefficients (HFC) is proposed to represent the objects in video frames. In addition, the performance of the video retrieval system based on the proposed HFC is validated using Classification and Regression Trees, Random Forest and Extreme Learning Machine model. Experimental results prove that HFC is an efficient content descriptor for high performance video retrieval.