A Novel Approach for Shot Boundary Detection in Videos

Abstract

Abstract. This paper presents a novel approach for video shot boundary detection. The proposed approach is based on split and merge concept. A fisher linear discriminant criterion is used to guide the process of both splitting and merging. For the purpose of capturing the between class and within class scatter we employ 2D 2 FLD method which works on texture feature of regions in each frame of a video. Further to reduce the complexity of the process we propose to employ spectral clustering to group related regions together to a single there by achieving reduction in dimension. The proposed method is experimentally also validated on a cricket video. It is revealed that shots obtained by the proposed approach are highly cohesive and loosely coupled.

Histogram Based Split and Merge Framework for Shot Boundary Detection

“…We first present the overview of split and merge framework introduced in [28]. In this framework, the authors have approached the shot boundary detection problem in a new way using split and merge concept.…”

“…With this a video frame with size mXn is represented with the help of only k feature vectors corresponding to k clusters of the frame and the dimension of the extracted feature vectors was very less when compared to that of the original frame. The major disadvantage of the work proposed in [28] was the amount of time required to process each video frame since they process every video frame in various levels to get its dimensionality reduced. In our present method, we try to extract features out of each video frame through the color histogram which can be processed in less time.…”

“…In [28], the authors reduce the dimensionality of the input video frame sequence by using Haralick texture features and spectral clustering techniques. Initially every frame is divided into 32X32 blocks and Haralick texture features are extracted from each block.…”

“…In our method, we have used a memory efficient color histogram representation to represent the video frames in reduced dimensions. Followed by this, we have exploited the split and merge framework introduced in [28] for automatic shot detection from videos. The proposed method is experimentally validated on videos of Trecvid dataset and some of the videos downloaded randomly from internet.…”

A Scheme for Shot Detection and Video Retreival using Spatio Temporal Features

“…With technological progress, there has been a revolution in multimedia content in the web, has resulted in many large personal and public digital video databases [1] [6]. However the rapid development in the availability of the multimedia database is not accompanied by the technologies used for its efficient usage and retrieval.…”