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Driving requires the constant coordination of many body systems and full attention of the person. Cognitive distraction (subsidiary mental load) of the driver is an important factor that decreases attention and responsiveness, which may result in human err ...
Recent deep neural networks based methods have achieved state-of-the-art performance on various facial expression recognition tasks. Despite such progress, previous researches for facial expression recognition have mainly focused on analyzing color recordi ...
In anesthesiology, the detection and anticipation of difficult tracheal intubation is crucial for patient safety. When undergoing general anesthesia, a patient who is unexpectedly difficult to intubate risks potential life-threatening complications with po ...
In this paper, we introduce our recent studies on human perception in audio event classification. In particular, the pre-trained model VGGish is used as feature extractor to process audio data, and DenseNet is trained by and used as feature extractor for o ...
Eye gaze and facial expressions are central to face-to-face social interactions. These behavioral cues and their connections to first impressions have been widely studied in psychology and computing literature, but limited to a single situation. Utilizing ...
In this paper, we propose a novel unsupervised approach for sequence matching by explicitly accounting for the locality properties in the sequences. In contrast to conventional approaches that rely on frame-to-frame matching, we conduct matching using sequ ...
Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...
We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...
Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...
Traditional techniques for emotion recognition have focused on the facial expression analysis only, thus providing limited ability to encode context that comprehensively represents the emotional responses. We present deep networks for context-aware emotion ...
