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Activity recognition from mobile device sensors and wearables is attracting more attention from the research community due to the widespread adoption of these devices and the unique opportunity they provide for understanding user’s behavior leading to novel services and improvements in the delivery of existing ones. Approaches to tackle this problem either rely on predefined statistical features of...
Emotion cause extraction is one of the promising research topics in sentiment analysis, but has not been well-investigated so far. This task enables us to obtain useful information for sentiment classification and possibly to gain further insights about human emotion as well. This paper proposes a bootstrapping technique to automatically acquire conjunctive phrases as textual cue patterns for emotion...
Video story segmentation, i.e., segmentation of video to semantically meaningful units, is an essential technology for advanced video processing, such as video retrieval, summarization, and so on. In this paper, we will introduce a generic video story segmentation method, which has achieved highly accurate segmentation on both broadcast news and non-news variety TV programs. Furthermore, we will probe...
In this paper, we propose new approximate clustering algorithm that improves the precision of a top-down clustering. Top-down clustering is proposed to improve the clustering speed by Iwayama et al, where the cluster tree is generated by sampling some documents, making a cluster from these, assigning other documents to the nearest node and if the number of assigned documents is large, continuing sampling...
In order to achieve highly accurate content-based music information retrieval (MIR), it is necessary to compensate the various bit rates of encoded songs which are stored in the music collection, since the bit rate differences are expected to apply a negative effect to content-based MIR results. In this paper, we examine how the bit rate differences affect MIR results, propose methods to normalize...
Technology to analyze the content of TV programs, especially the extraction and annotation of important scenes and events within a program, is beneficial for users to enjoy recorded programs. In this paper, we propose a method of detecting significant scenes in TV programs and automatically annotating the content of the extracted scenes through Twitter analysis. Experiments conducted on baseball games...
This research proposes a novel method to extract image regions of products from an advertisement video, by analyzing features which are completely independent from the target object. Namely, we focus on how each product is emphasized in the video production, and propose the utilization of low-level visual features which leverage the technical know-how of video producers. By using such features, our...
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