Content-Based Retrieval of Video Shot Using the Improved Neatest Feature Line Method
利用改进NFL算法对镜头进行基于内容的检索

The shot based classification and retrieval is very important for video database organization and access. In this paper, a new approach NFL (nearest feature line) used in shot retrieval is presented. Key-Frames in shot are looked as feature points to represent the shot in feature space. Lines connecting the feature points are further used to approximate the variations in the whole shot. The similarity between the query image and the shots in video database are measured by calculating the distance between the query image and the feature lines in feature space. To make it more suitable to video data, the original NFL method by adding constrains on the feature lines is improved. Experimental results show that the improved NFL method is better than the traditional classification methods such as the nearest neighbor (NN) and the nearest center (NC).