Machine recognition of faces in video is an emerging problem. Following recent advances, conventional exemplar-based schemes and image set approaches inadequately exploit temporal information in video sequences for the classification task. In this work, we propose a new dualfeature Bayesian maximum-a-posteriori (MAP) classification method for face recognition in video sequences. Both cluster an...

In this paper, we propose our techniques and results on automatic analysis of cricket video to facilitate highlight generation and content-based retrieval. We use Dynamic Programming based on Hidden Markov Model (HMM-DP) approach for structure analysis of cricket video sequences. We introduce a scaling factor α with the likelihood values to achieve classification more robust and accurate. We ob...

the video quality assessment must be adapted to the human visual system, which is why researchers have performed subjective viewing experiments in order to obtain the conditions of encoding of video systems to provide the best quality to the user. the objective of this study is to assess the video quality using image features extraction without using reference video. rmse values and processing ...

Video scene classification technology is becoming more important with development of multi-media system. In order to classify the video scene, the models to identify the video scene are needed. In the case of constructing the video scene classification system for TV programs, it is difficult to make the models because the T V programs have many kinds of scene. For above mentioned problem, a new...

Previous research has shown that information can be extracted from encrypted multimedia streams. This includes video titles classification of non-HTTP adaptive streams (nonHAS). This paper presents an algorithm for encrypted HTTP adaptive video streaming title classification. We evaluated our algorithm on a new YouTube popular videos dataset that was collected from the Internet under real-world...

Previous research has shown that information can be extracted from encrypted multimedia streams. This includes video titles classification of non HTTP adaptive streams (nonHAS). This paper presents an algorithm for encrypted HTTP adaptive video streaming title classification. We evaluated our algorithm on a new YouTube popular videos dataset that was collected from the internet under real-world...