Sequential association mining for video summarization
نویسندگان
چکیده
In this paper, we propose an association-based video summarization scheme that mines sequential associations from video data for summary creation. Given detected shots of video V, we first cluster them into visually distinct groups, and then construct a sequential sequence by integrating the temporal order and cluster type of each shot. An association mining scheme is designed to mine sequentially associated clusters from the sequence, and these clusters are selected as summary candidates. With a user specified summary length, our system generates the corresponding summary by selecting representative frames from candidate clusters and assembling them by their original temporal order. The experimental evaluation demonstrates the effectiveness of our summarization method.
منابع مشابه
Semantic Concept Mining Based on Hierarchical Event Detection for Soccer Video Indexing
In this paper, we present a novel automated indexing and semantic labeling for broadcast soccer video sequences. The proposed method automatically extracts silent events from the video and classifies each event sequence into a concept by sequential association mining. The paper makes three new contributions in multimodal sports video indexing and summarization. First, we propose a novel hierarc...
متن کاملFuzzy Sequential Patterns Summarization with Lattice Structure
Data mining is new but an interdisciplinary field utilizing statistics, machine learning, and other methods. In recent years, fuzzy logic has also been applied to augment data mining. The application of fuzzy logics makes the mining results more understandable and interpretable, apart from being useful and informative. Fuzzy rules are useful to summarize large databases. Several studies are don...
متن کاملDiverse Sequential Subset Selection for Supervised Video Summarization
Video summarization is a challenging problem with great application potential. Whereas prior approaches, largely unsupervised in nature, focus on sampling useful frames and assembling them as summaries, we consider video summarization as a supervised subset selection problem. Our idea is to teach the system to learn from human-created summaries how to select informative and diverse subsets, so ...
متن کاملPersonalization Based on Domain Ontology
As a consequence of the proliferation of multimedia contents, users are nowadays frustrated with the huge amount of available video information whose content is not targeted to their needs and preferences. Its challenging to analysis video content for video personalization due to the lack of semantic video summarization and retrieval techniques. In fact, most of current video personalization sy...
متن کاملDocument Clustering and Summarization Based on Association Rule Mining for Dynamic Environment
Document Summarization is a technique, which reduces the size of the documents and gives the outline and crisp information about the given group of documents. This paper introduces a new update summarization algorithm incorporating association rule mining and correlated concept based hierarchical clustering for dynamic environment. In this algorithm, the associated concepts are extracted using ...
متن کامل