Unsupervised and Model-Free News Video Segmentation
نویسندگان
چکیده
Based on a simple temporal structural model of news program, this paper presents a practical solution to automatic news story segmentation by integrating syntactic and semantic methods. First, a syntactic segmentation method is used to detect the shot boundaries in order to partition video frames into video shots. Then a semantic segmentation method based on the graph-theoretical cluster analysis is developed to classih the video shots into anchorperson shots and news footage shots. Finally, a structural model of news video is used to complete the news-story segmentation. The proposed method obtains a precision of 90.45% and a recall of 95.83% in the segmentation experiment of I68 news stories from two Hong Kong news stations.
منابع مشابه
Unsupervised video-shot segmentation and model-free anchorperson detection for news video story parsing
News story parsing is an important and challenging task in a news video library system. In this paper, we address two important components in a news video story parsing system: shot boundary detection and anchorperson detection. First, an unsupervised fuzzy -means algorithm is used to detect video-shot boundaries in order to segment a news video into video shots. Then, a graph-theoretical clust...
متن کاملUnsupervised Texture Image Segmentation Using MRFEM Framework
Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...
متن کاملUnsupervised Texture Image Segmentation Using MRFEM Framework
Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...
متن کاملUnsupervised News Video Segmentation by Combined Audio-Video Analysis
Segmenting news video into stories is among key issues for achieving efficient treatment of news-based digital libraries. In this paper we present a novel unsupervised algorithm that combines audio and video information for automatic partitioning news videos into stories. The proposed algorithm is based on the detection of anchor shots within the video. In particular, a set of audio/video templ...
متن کاملTraffic Scene Analysis using Hierarchical Sparse Topical Coding
Analyzing motion patterns in traffic videos can be exploited directly to generate high-level descriptions of the video contents. Such descriptions may further be employed in different traffic applications such as traffic phase detection and abnormal event detection. One of the most recent and successful unsupervised methods for complex traffic scene analysis is based on topic models. In this pa...
متن کامل