Korea Advanced Institute of Science and Technology

Samsung Electronics Co., Ltd.

Hak Gu Kim

YongMan Ro

Sangmin Lee

Jin-Sung Lee

Jong-sul Min

A virtual reality (VR) sickness assessment method according to an embodiment includes receiving virtual reality content, and quantitatively evaluating virtual reality sickness for the received virtual reality content using a neural network based on a pre-trained neural mismatch model. The evaluating of the virtual reality sickness may include predicting an expected visual signal for an input visual signal of the virtual reality content based on the neural mismatch model, extracting a neural mismatch feature between the predicted expected visual signal based on the neural mismatch model and an input visual signal for a corresponding frame of the virtual reality content corresponding to the expected visual signal, and evaluating a level of the virtual reality sickness based on the neural mismatch model and the extracted neural mismatch feature.

Method for VR sickness assessment considering neural mismatch model and the apparatus thereof

Disclosed is an apparatus and method for VR sickness reduction based on VR sickness assessment. According to an embodiment of the inventive concept, an apparatus for reducing virtual reality (VR) content cybersickness includes a first module extracting feature information about each of predetermined cybersickness precipitating factors through analysis of VR content, and a second module determining a cybersickness precipitating factor requiring cybersickness reduction among the cybersickness precipitating factors based on the extracted feature information about each of the cybersickness precipitating factors, and generating the VR content as VR content having a cybersickness score not greater than a predetermined reference cybersickness score, by performing the cybersickness reduction on corresponding feature information, using a deep learning neural network pre-learned for each of the respective determined cybersickness precipitating factor.

Apparatus and method for virtual reality sickness reduction based on virtual reality sickness assessment

A VR content sickness evaluating apparatus using a deep learning analysis of a motion mismatch and a method thereof are provided. The VR content sickness evaluating apparatus analyzes a motion mismatch phenomenon between visual recognition information and posture recognition information, which occurs when a user views VR content, using deep learning and predicts and evaluates a degree of VR sickness from a difference between motion features.

VR content sickness evaluating apparatus using deep learning analysis of motion mismatch and method thereof

A hologram generating apparatus is provided. The apparatus includes a hologram signal generating unit configured to, based on light projected on at least some points corresponding to an object, generate a hologram signal corresponding to the at least some points on at least one two-dimensional plane, a processor configured to calculate a sparsity corresponding to the two-dimensional plane based on the hologram signal, and to calculate a fringe pattern based on at least some of the hologram signal, and a pattern writing unit configured to record the fringe pattern on a computer-generated holography (CGH) plane, wherein the processor is further configured to repeatedly calculate a fringe pattern until a number of dominant signals of the calculated fringe pattern coincides with a predetermined threshold value determined based on the sparsity.

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Daejeon, South Korea

Hak Gu Kim