Story Segmentation in News Videos Using Visual and Text Cues

Abstract. In this paper, we present a framework for segmenting the news programs into different story topics. The proposed method utilizes both visual and text information of the video. We represent the news video by a Shot Connectivity Graph (SCG), where the nodes in the graph represent the shots in the video, and the edges between nodes represent the transitions between shots. The cycles in the graph correspond to the story segments in the news program. We first detect the cycles in the graph by finding the anchor persons in the video. This provides us with the coarse segmentation of the news video. The initial segmentation is later refined by the detections of the weather and sporting news, and the merging of similar stories. For the weather detection, the global color information of the images and the motion of the shots are considered. We have used the text obtained from automatic speech recognition (ASR) for detecting the potential sporting shots to form the sport stories. Adj...

• Type: Conference
• Year: 2005
• Where: CIVR
• Authors: Yun Zhai, Alper Yilmaz, Mubarak Shah
• Keywords: CIVR 2005, Graph Correspond, Potential Sporting Shots, Shot Connectivity Graph