Abstract book (pdf) - ICPR 2010

13:30-16:30, Paper WeBCT9.30
A Multimodal Approach to Violence Detection in Video Sharing Sites
Giannakopoulos, Theodoros, Univ. of Athens
Pikrakis, Aggelos, Univ. of Piraeus
Theodoridis, Sergios, Univ. of Athens
This paper presents a method for detecting violent content in video sharing sites. The proposed approach operates on a fusion
of three modalities: audio, moving image and text data, the latter being collected from the accompanying user comments.
The problem is treated as a binary classification task (violent vs non-violent content) on a 9-dimensional feature
space, where 7 out of 9 features are extracted from the audio stream. The proposed method has been evaluated on 210
YouTube videos and the overall accuracy has reached 82%.
13:30-16:30, Paper WeBCT9.31
Video Retrieval based on Tracked Features Quantization
Hiroaki, Kubo, Keio Univ.
Pilet, Julien, Keio Univ.
Satoh, Shin’Ichi, National Inst. of Informatics
Saito, Hideo, Keio Univ.
In this paper, we present an image retrieval method based on feature tracking. Feature tracks are summarized into a compact
discreet value and used for video indexing purpose. As opposed to existing space-time features, we do not make any assumption
on the motion visible on the indexed videos. As a result, given an example query, our system is able to retrieve
related videos from a large database. We evaluated our system with the copy detection benchmark MUSCLE-VCD-2007.
We also ran retrieval experiment on hours of TV broadcast.
13:30-16:30, Paper WeBCT9.32
Interactive Web Video Advertising with Context Analysis and Search
Wang, Bo, Chinese Acad. of Sciences
Wang, Jinqiao, Chinese Acad. of Sciences
Duan, Lingyu, Peking Univ.
Tian, Qi, Univ. of Texas at San Antonio
Lu, Hanqing, Chinese Acad. of Sciences
Gao, Wen, PeKing Univ.
Online media services and electronic commerce are booming recently. Previous studies have been devoted to contextual
advertising, but few work deals with interactive web advertising. In this paper, we propose to put users in the loop of collecting
contextual ad information with an interaction process, establishing semantic ad links across media platforms. Given
an ad video, the key frames with explicit product information are located, which allow users to click favorite key frames
for searching ads interactively. A three-stage contextual search is applied to find relevant products or services from web
pages, i.e., searching visually similar product images on shopping websites, ranking product tags by text aggregation, and
re-search textual items consisting of semantic meaningful tags to make a recommendation. In addition, users can choose
automatically suggested keywords to reflect their intentions. Subjective evaluation has demonstrated the effectiveness of
the proposed approach to interactive video advertising over the Web.
13:30-16:30, Paper WeBCT9.33
Selection of Photos for Album Building Applications
Egorova, Marta, National Nuclear Res. Univ.
Safonov, Ilia, National Nuclear Res. Univ.
In this work we propose a new algorithm for selection of high-quality photos for album building applications. We describe
how to select features for detection well-exposed, sharp and artifact-free photos. We considered two approaches: the first,
typical way when all features are used in single AdaBoost classifiers committee and the second way, when decision tree,
including 3 committees. Careful analysis of features and decision tree construction allowed better outcomes to be reached.
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