Wistron Corporation

Ching-An Cho

Yu-Yen Chen

Kuo-Ting Huang

You-Jyun Syu

Zhen-Te Liu

Hao-Gong Chou

Kuo-Hsien Lu

Shih-Wen Chen

Chia-Ta Hsieh

Hsuan-Tsung Chang

Yu-Ren Lai

Po Chun Chen

Kuo Ting Huang

Bo-Yi Wu

Chih-Hao Chiu

Wei-Kuo Kan

Ming-Che Ho

Chan-Hsuan Yu

Zheng-De Liu

A wearable device with heart rate detection includes a heart rate detection assembly and a processor. The heart rate detection assembly is configured to obtain a plurality of dynamic heart rate signals according to a default frequency. The processor includes a finite state machine and a storage. The storage is configured to store the plurality of dynamic heart rate signals, and the finite state machine determines a heart rate state according to a sampling parameter and the plurality of dynamic heart rate signals. The processor obtains a weight according to the heart rate state, and obtains a dynamic heart rate value according to the weight.

Wearable device with heart rate detection, dynamic heart rate detection method and non-transitory computer-readable storage medium

The present invention provides a signal quality detection method for an ear-chip physiological measurement device. The signal quality detection method includes receiving a sensing signal from the ear-clip physiological measurement device; filtering the sensing signal to generate a pre-processed signal; calculating a physiological index according to the pre-processed signal; and calculating a similarity of a red light alternating current (AC) component and an infrared light AC component of the pre-processed signal and a plurality of correlation coefficients of the red light AC component, and generating a reliability index of the physiological index accordingly. The reliability index indicates one of a plurality of signal qualities.

Signal quality detection method and signal detection device thereof

A method for calculating blood oxygen saturation includes defining the extreme value point of a non-red light signal as the extreme value point of a red light signal, and calculating the blood oxygen saturation according to the extreme value point of the red light signal. The method for calculating blood oxygen saturation of the present disclosure proposes to use other light source signals to assist in finding the period of the red light signal, so that the calculation result of the red light signal is more accurate.

Method, computer programming product and electronic device for calculating blood oxygen saturation

A method of determining noise reduction in a signal includes transforming the signal to generate a spectrogram; determining sharp change in a frequency spectrum for each frame in the spectrogram; and comparing a counted number of frames having sharp change with a predetermined value. The signal is determined to be subject to noise reduction if the counted number is greater than the predetermined value.

Signal processing system and a method of determining noise reduction and compensation thereof

An image analysis method applicable to an electronic system is provided. The electronic system includes an image capture device. The image analysis method includes: obtaining a plurality of images captured by the image capture device; performing a motion detection on the plurality of images to determine whether the images include a motion; and determining whether a target enters the preset scenery or leaves the preset scenery in response to a determination that the plurality of images include the motion according to the motion detection.

Image analysis method for motion determination, electronic system, and non-transitory computer-readable recording medium

A method and a computer system for object tracking are provided. The method includes the following steps. An image sequence including multiple images with a target object is obtained. A labelling operation corresponding to the target object in first two images and last two images in the image sequence is received to respectively generate four ground truth labels of the target object. A forward tracking of the target object is performed on the image sequence in time series according to the ground truth labels of the first two images to obtain a forward tracking result. A backward tracking of the target object is performed on the image sequence in time series according to the ground truth labels of the last two images to obtain a backward tracking result. The forward and the backward tracking results are compared to accordingly generate a final tracking result of the target object.

Method and computer system for object tracking

A method and a computing device for monitoring an object are provided, where the method includes the following steps. An image sequence captured on a monitored area is received. Whether a target object is within a region of interest (ROI) of the monitored area is determined. If the determination is not affirmative and at least one first moving object is detected, whether the first moving object enters the ROI is determined according to a relative position between the first moving object and a detection boundary as well as whether the first moving object has continuous movements in the ROI. If the determination is affirmative, whether the target object leaves the ROI is determined according to a relative position between at least one second moving object associated with the target object and the detection boundary as well as whether the second moving object has continuous movements in a non-ROI.

Method and computing device for monitoring object

An image detection method for determining the postures of a user includes: obtaining a plurality of images of a user; determining whether the user moves; and when the user is determined to be moving, calculating whether the amount of images is greater than a first predetermined value or not, calculating whether or not the amount of images of the user in the region of interest (ROI) is greater than a second predetermined value, and calculating whether or not the amount of images of the user not in the ROI is greater than a third predetermined value, in order to determine the postures of the user.

Image detection method and image detection device for determining posture of a user

A method for detecting multiple touch positions on a touch surface, which is applicable to a touch apparatus having multiple optical sensing modules, where each optical sensing module includes at least two optical sensing devices. The method includes: acquiring multiple pieces of sense information; determining multiple touch ranges for each piece of sense information; determining multiple points of intersection; selecting one of the pieces of sense information of which the touch ranges are used to calculate a greatest numbers of the points of intersection; for each touch range of the selected sense information, repeatedly selecting two of the points of intersection calculated using the corresponding touch range according to distances until the selected two points of intersection are verified as being located within the touch ranges of at least another one piece of sense information other than the selected sense information; and calculating the touch positions as actual touch positions according to the selected points of intersection when the selected points of intersection are verified as being located within the touch ranges of the at least another one piece of sense information other than the selected sense information.

Method of detecting touch position and touch apparatus thereof

An image detection method for determining the posture of a user includes: obtaining a reference image of the user in a region of interest (ROI); obtaining a test image of user at the ROI; executing a feature matching analysis of the test image which compares the feature parameter of the test image and the feature parameter of the reference image to determine the similarity information of the test image and the reference image; and executing a pixel distribution analysis of the test image to obtain user pixel distribution information; and determining the posture of the user based on the user similarity information and the user pixel distribution information.

A method, a system, and a computer-readable recording medium for long-distance person identification are provided. The method is applicable to a system having an image capturing device and a depth sensor and includes the following steps. An image of a user is captured by using the image capturing device to generate a user image, and depth information of a user is detected by using a depth sensor to generate user depth information. Soft biometric features of the user are obtained according to the user image and the user depth information, where the soft biometric features include silhouette information and human body features. A soft biometric feature similarity of the user is calculated based on the soft biometric features by using registered information of registered users so as to output a person identification result accordingly.

Method, system, and computer-readable recording medium for long-distance person identification

A video editing method, a video editing device, and a video editing system are provided. A target is obtained from an original video. Relative position relations respectively between each frame and a previous frame and a next frame adjacent to it are obtained based on multiple image feature points of each frame. An adjustment process is executed respectively for each frame. The adjustment process includes: obtaining a frame N; identifying the target in the frame N; adjusting the frame N to obtain a new frame, wherein the target is located on a center of the new frame; and modifying the new frame based on the relative position relations to obtain a postproduction frame. A processed video is outputted based on multiple postproduction frames.

Method, device and system for editing video

An optical touch panel and a detection method thereof are provided. The detection method includes following steps. A main panel is sensed by a first optical sensor and a second optical sensor. If the first optical sensor and the second optical sensor both sense two objects approaching the main panel, and a quantity of at least one first reflection signal sensed by the first optical sensor and a quantity of at least one second reflection signal sensed by the second sensor are inconsistent, the at least one first reflection signal or the at least one second reflection signal that is not paired at a current time point is removed according to a pairing relationship between the at least one first reflection signal and the at least one second reflection signal at a previous time point.

Optical touch panel and detection method thereof

An optical touch device and a sensing method thereof are provided. The optical touch device includes a plurality of optical sensors and a processing unit. The optical sensors are arranged around a touch plane and are spaced from each other. The two adjacent optical sensors located at one side of the touch plane are defined as one set of an optical sensing module, such that the optical sensors are paired to form multiple sets of the optical sensing modules. The processing unit generates a plurality of touch coordinates data corresponding to the plurality sets of the optical sensing modules according to the optical touch data, and determines whether the touch coordinates data corresponding to each set of the optical sensing modules is in at least one touch-excluded area corresponding to each set of the optical sensing modules, and respectively excludes the touch coordinates data in the touch-excluded area.

Optical touch device and sensing method thereof

An optical touch system includes a touch surface, a first light source and a first light-sensing unit. The first light source emits a first light. The first light is reflected at positions on a first section of the touch surface to form a first reference section at the first light-sensing unit. The first light is reflected at positions on a second section of the touch surface to form a second reference section at the first light-sensing unit. The second section is located between the first section and the first light-sensing unit. A touch object reflects the first light between the first section and the second section to produce a first input light region on the first reference section, or reflects the first light between the second section and the first light-sensing unit to produce a second input light region on the second reference section.

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Taipei, Taiwan

Ching-An Cho