Horror Video Recognition Based on Fuzzy Comprehensive Evolution

Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-lev...

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Bibliographic Details
Published in:China communications 2014, Vol.11 (2), p.86-94
Main Authors: Song, Wei, Yang, Pei, Yang, Guosheng, Ma, Chuanlian, Yu, Jing, Li, Ming
Format: Article
Language:English
Subjects:
Color
Feature extraction
fuzzy comprehensive evolution
Hidden Markov models
horror video recognition
Image color analysis
Internet
K-Means cluster
Rhythm
video affective
Visualization
典型特征
层次分析法
模糊综合
演化模型
特征提取
网页内容过滤
视频识别
进化
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Summary:Technique for horror video recognition is important for its application in web content filtering and surveillance, especially for preventing children from being threaten. In this paper, a novel horror video recognition algorithm based on fuzzy comprehensive evolution model is proposed. Three low-level video features are extracted as typical features, and they are video key-light, video colour energy and video rhythm. Analytic Hierarchy Process （AHP） is adopted to estimate the weights of extracted features in fuzzy evolution model. Horror evaluation （membership function） is on shot scale and it is constructed based on the knowledge that videos which share the same affective have similar low-level features. K-Means algorithm is implemented to help finding the most representative feature vectors. The experimental results demonstrate that the proposed approach has good performance in recognition precision, recall rate and F1 measure.
ISSN:1673-5447
DOI:10.1109/CC.2014.7085388