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 recognitio...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.展开更多
This article proposes a new general, highly efficient algorithm for extracting domain terminologies. This domain-independent algorithm with multi-layers of filters is a hybrid of statistic-oriented and rule-oriented m...This article proposes a new general, highly efficient algorithm for extracting domain terminologies. This domain-independent algorithm with multi-layers of filters is a hybrid of statistic-oriented and rule-oriented methods. Utilizing the features of domain terminologies and the characteristics that are unique to Chinese, this algorithm extracts domain terminologies by generating multi-word unit （MWU） candidates at first and then fihering the candidates through multi-strategies. Our test resuhs show that this algorithm is feasible and effective.展开更多
文摘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.
基金Supported by the National Natural Science Foundation of China(Grant No. 60496326)
文摘This article proposes a new general, highly efficient algorithm for extracting domain terminologies. This domain-independent algorithm with multi-layers of filters is a hybrid of statistic-oriented and rule-oriented methods. Utilizing the features of domain terminologies and the characteristics that are unique to Chinese, this algorithm extracts domain terminologies by generating multi-word unit （MWU） candidates at first and then fihering the candidates through multi-strategies. Our test resuhs show that this algorithm is feasible and effective.
