Wistron Corporation

Chih-Yang Hung

Yao-Tsung Chang

Chuan-Yen Kao

Chu-Chia Tsai

Ping-Hung Chen

I-Chun Wu

Ching-Fu Hsu

A training device includes a force receiving component, a location detector, a resistance generator, and a controller. The force receiving component moves along a closed trajectory. The location detector is configured to detect a location of the force receiving component in the closed trajectory and to output a location signal. The resistance generator is configured to exert a resistance on the force receiving component. The controller controls the resistance generator to adjust the resistance based on the location signal.

Training device with adjustable resistance

A live facial recognition method includes projecting a given pattern to a subject under recognition; capturing a reflected pattern of the subject under recognition; and detecting whether the subject under recognition is a flat surface according to the reflected pattern. The subject under recognition is determined to be a living subject when the subject under recognition is not a flat surface.

Live facial recognition system and method

A live facial recognition method includes capturing a zoom-out image of a face of a subject under recognition; and detecting a frame outside the face of the subject under recognition on the zoom-out image. The subject under recognition is determined to be a living subject when the zoom-out image includes no frame outside the face.

A live facial recognition method includes capturing a plurality of images of a face of a subject under recognition; obtaining time-varying data according to the images, the time-varying data representing a periodic variation of facial color of the subject under recognition due to facial vasoconstriction and vasodilation caused by heartbeat; and comparing the time-varying data with a predetermined frequency range. The subject under recognition is determined to be a living subject when the time-varying data is within the predetermined frequency range.

An example of the invention provides an electronic device. The electronic device includes a camera module, a control unit and a computing unit. The control unit controls the camera module to acquire a first image and a second image. The computing unit receives the first image and the second image to generate a third image, wherein the resolution of the third image is greater than the resolution of the first image and the resolution of the second image.

Electronic device and image processing method thereof

An image processing method is provided. The method includes following steps. Firstly, a first image is obtained by shooting photo at a first shutter speed, wherein the first image includes a first object image and a first background image, and the first object image and the first background image are clear. Next, a second image is obtained by shooting photo at a second shutter speed lower than the first shutter speed, wherein the second shutter speed is lower than the first shutter speed, the first image and the second image are obtained by shooting photo within substantially the same shooting range, the second image includes a second object image and a second background image, the second object image is blurry but the second background image is clear. After that, a third image is generated from at least the first image and the second object image.

Electronic device and image processing method

An image processing method is provided. A first image is obtained at a first time point, the first image includes a first object image and a first background image, the first object image corresponds to the position of an object at the first time point. A second image is obtained at a second time point, the second image includes a second object image and a second background image, the second object image corresponds to the position of the object at the second time point, and the first and the second images are shot within substantially the same shooting range. A sum motion vector of the object is obtained according to the first and the second object images. The second object image is kept, and a process is applied to each pixel of the second background image in the second image to generate a third image.

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Taipei, Taiwan

Chih-Yang Hung