A Novel Approach for Shot Boundary Detection in Videos

TL;DR

This paper introduces a new shot boundary detection method for videos that combines split-merge techniques guided by Fisher linear discriminant analysis and spectral clustering, validated on cricket videos.

Contribution

It proposes a novel split-merge approach guided by FLD and spectral clustering for efficient shot boundary detection in videos.

Findings

Shots are highly cohesive and loosely coupled.

Method effectively captures scene changes.

Validated on cricket video dataset.

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 2D2 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