National Taiwan University

Himax Technologies, Inc.

Ganzin Technology, Inc.

Su-Ling Yeh

Homer H Chen

Tai-Hsiang Huang

Ling-Hsiu Huang

Lin-Kai Bu

Shao-Yi Chien

Polly Huang

Kuei-An Li

Sheng-Chun Niu

Kuang-Tsu Shih

Chien-Nan Chen

Cing-Yu Chu

Wen-Fu Lee

Yung-Hao Yang

Hsin-I Liao

San-Yuan Lin

A method of monitoring eye strain includes detecting the blink status, the vergence status and the pupil status of a user, and then determining whether the user encounters eye strain according to at least one of the blink status, the vergence status and the pupil status of the user. The method further includes facilitating the user to blink or informing the user of eye strain.

Method of monitoring eye strain and related optical system

A method and system of enhancing a backlight-scaled image include a minimum perceptible luminance threshold of cone response with dim backlight being determined, and a luminance layer associated with an image being extracted. The luminance layer is decomposed into an HVS response layer and a background luminance layer for each pixel of the luminance layer. Luminance of dark pixels of the background luminance layer is boosted and compressed to a perceptible range above the minimum perceptible luminance threshold, thereby resulting in an enhanced background luminance layer. An enhanced luminance layer is generated through composition using the HVS response layer and the enhanced background luminance layer as inputs.

Method and system of enhancing a backlight-scaled image

A multimedia bitrate adaption method for individual users wherein only a set of predetermined bitrates may be selected as the multimedia bitrate of the user. The predetermined bitrates are quantized into exponentially distributed levels, and the users' experiences corresponding to the predetermined bitrates are with the same intervals, thereby increasing the service capacity and improving user satisfaction.

Multi-media data rate allocation method and voice over IP data rate allocation method

A learning-based visual attention prediction method is disclosed. The method includes a correlation relationship between the fixation density and at least one feature information being learned by training, followed by a test video sequence of test frames being received. Afterward, at least one tested feature map is generated for each test frame based on the feature information. Finally, the tested feature map is mapped into a saliency map, which indicates the fixation strength of the corresponding test frame, according to the correlation relationship.

Learning-based visual attention prediction system and method thereof

An object-based system and method of directing visual attention by a subliminal cue is disclosed. An object detector detects an object in an input image, thereby resulting in a cued object served as an object-based subliminal cue. An enhancement unit enhances saliency of the cued object in the input image by respectively and differently adjusting image characteristic of the cued object and an area other than the cued object, thereby generating a cue image. A mixer selects between the cue image and the input image, thereby resulting in a sequence of output images composed of the input images and the cue images, each of which is interposed between the adjacent input images.

Object-based system and method of directing visual attention by a subliminal cue

A method of directing a viewer's attention in an image display to enhance the perceived image quality and thus the viewer's preference of the image is disclosed. An image with an area of interest (AOI) is provided. The AOI is briefly displayed for a first time period. Subsequently, the image is normally displayed in its entirety for a second time period that is longer than the first time period. As a result, the viewer's attention is involuntarily directed to the AOI in a subliminal manner.

Method of directing a viewer's attention subliminally in image display

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Taipei, Taiwan

Su-Ling Yeh