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In this paper we evaluate the impact of different encoding configurations such as compression ratios, frame rates and resolution on the perceived quality of high definition video-conference applications. After generating a high quality video database, degraded sequences had their quality assessed by state-of-the-art automatic metrics. Results have shown that, for low rates, it is preferable to decrease...
Although traditional bag-of-words model has shown promising results for action recognition, it takes no consideration of the relationship among spatio–temporal points; furthermore, it also suffers serious quantization error. In this letter, we propose a novel coding strategy called context-constrained linear coding (CLC) to overcome these limitations. We first calculate the contextual distance between...
A framework for generating facial expressions from emotional states in daily conversation is described. The framework allows avatars to express the speaker's state not just prototypical emotions. In this paper, the naturalness of generated facial expressions that are presented together with dialogue speech is examined. An experiment to examine the naturalness of facial expressions presented as still...
Recently, computer go has experienced great advance with the introduction of Monte-Carlo Tree Search (MCTS). Although MCTS programs are overall stronger than previous programs, their strength manifests mostly as the game advances. Strong human players applying established opening principles overtake current MCTS programs in the early moves of non-handicap 19×19 games. In this paper, the authors propose...
Because of the critical role that communication plays in a team's ability to coordinate action, the measurement and analysis of online transcripts in order to predict team performance is becoming increasingly important in domains such as global software development. Current approaches rely on human experts to classify and compare groups according to some prescribed categories, resulting in a laborious...
In this paper we evaluate the use of Restricted Bolzmann Machines (RBM) in the context of learning and recognizing human actions. The features used as basis are binary silhouettes of persons. We test the proposed approach on two datasets of human actions where binary silhouettes are available: ViHASi (synthetic data) and Weizmann (real data). In addition, on Weizmann dataset, we combine features based...
The application of sound classification for detecting intruders into protected wildlife regions has been addressed recently. For such an application, simple, yet robust, methods must be utilized since these systems usually are required to work in difficult conditions. The Time Encoded Signal Processing and Recognition (TESPAR) algorithm represents a good candidate due to its simplicity. In this paper...
We investigate in this paper the problem of estimating human ages from gait signatures. To our knowledge, this problem has not been formally addressed in the literature. Estimating human ages at a distance has a number of potential applications, including visual surveillance and monitoring in such public places as airports, railway stations, shopping malls, and various building entrances. Motivated...
In this paper we propose the CTS (concious tutoring system) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning and remembering events and any related information such as corresponding procedures, stimuli and their emotional valences. Our proposed episodic memory and episodic learning mechanism are closer to the current multiple-trace...
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