Abstract: An image sleep analysis method and system thereof are disclosed. During sleep duration, a plurality of visible-light images of a body are obtained. Positions of image differences are determined by comparing the visible-light images. A plurality of features of the visible-light images are identified and positions of the features are determined. According to the positions of the image differences and features, the motion intensities of the features are determined. Therefore, a variation of the motion intensities is analyzed and recorded to provide accurate sleep quality.

Abstract: A breath detecting system and breath detecting mat thereof are disclosed. The breath detecting mat is placed under bed mattress and has a hollow board, a vibration sensor and a signal processing circuit. The vibration sensor and the signal processing circuit are mounted in the hollow board. The vibration sensor senses the micro-vibrations caused by the breathing of the person is lying on the bed mattress and outputs the breath sensing signal to the signal processing circuit. The signal processing circuit samples the sensing signal according to different moving average points to generate the fast-moving and slow-moving average signals. Since the first fast-moving and slow-moving average signals have many cross points, the signal processing circuit calculates each time difference between every two adjacent cross points. A present breath frequency is calculated according to the time differences. Therefore, the noises of the sensing signal are effectively removed.

Abstract: A visible-light-image physiological monitoring system with thermal detecting assistance is disclosed. The system takes a visible-light image and a thermal image of a body at the same time. A processing unit identifies a body feature of the visible-light image and determines a coordinate of the feature. In a learning mode, an initial temperature of the body feature is determined from the thermal image according to the coordinate of the body feature. After then, a physiological status monitoring mode is executed to monitor the temperature changes of the body feature and output an alarm when the temperature is determined to be abnormal. Therefore, a monitoring accuracy of the visible-light-image physiological monitoring system is increased and avoids transmitting false alarms or no alarms.

Abstract: An optical image physiological monitoring system with radar detection assistance is disclosed. The system receives a visible-light image of a body and then identifies a chest feature of the visible-light image and determines a position of the chest feature. A processing unit controls a radar detector to move to aim a chest of the body. After then, a plurality of visible-light images and distance values from the radar detector are received continuously to determine whether the positions of the chest features are in a position change rage. If yes, a breathing frequency of the body is determined by the distance values received simultaneously.

Abstract: An image detection method for selecting a representative image of a user is provided. In the image detection method, a plurality of images of the user are obtained, and a plurality of feature parameters of the plurality of images are obtained. A face occlusion analysis is performed on the plurality of images according to the plurality of feature parameters to determine whether the plurality of images clearly show the user's face. A plurality of feature vectors are determined, and a body distribution analysis is performed on the plurality of images according to the plurality of feature vectors to determine a body position and a position type of the user. An image related to the position type is selected according to results of the face occlusion analysis and the body distribution analysis.

Abstract: A visible-light-image physiological monitoring system with thermal detecting assistance is disclosed. The system takes a visible-light image and a thermal image of a body at the same time. A processing unit identifies a body feature of the visible-light image and determines a coordinate of the feature. In a learning mode, an initial temperature of the body feature is determined from the thermal image according to the coordinate of the body feature. After then, a physiological status monitoring mode is executed to monitor the temperature changes of the body feature and output an alarm when the temperature is determined to be abnormal. Therefore, a monitoring accuracy of the visible-light-image physiological monitoring system is increased and avoids transmitting false alarms or no alarms.

Abstract: An image sleep analysis method and system thereof are disclosed. During sleep duration, a plurality of visible-light images of a body are obtained. Positions of image differences are determined by comparing the visible-light images. A plurality of features of the visible-light images are identified and positions of the features are determined. According to the positions of the image differences and features, the motion intensities of the features are determined. Therefore, a variation of the motion intensities is analyzed and recorded to provide accurate sleep quality.

Abstract: An image detection method is provided. In the image detection method, images of a user are obtained, feature parameters are marked in the images, and detection results of the feature parameters in each of the images are evaluated. A body distribution analysis is performed on the images according to the detection result of at least one first feature parameter among the feature parameters to determine first position information of the user. A face occlusion analysis is performed on the images according to the detection result of at least one second feature parameter among the feature parameters and the first position information to determine second position information of the user. The at least one second feature parameter is different from the at least one first feature parameter. The second position information represents a position of the user.

Abstract: An image detection method for determining positions of a user. According to the image detection method, a plurality of images of the user are obtained, whether the user moves is determined according to the images, a plurality of feature parameters of the plurality of images are obtained, and a body distribution analysis and a face occlusion analysis are performed to determine the position of the user.

Abstract: An image detection method is provided. In the image detection method, images of a user are obtained, feature parameters are marked in the images, and detection results of the feature parameters in each of the images are evaluated. A body distribution analysis is performed on the images according to the detection result of at least one first feature parameter among the feature parameters to determine first position information of the user. A face occlusion analysis is performed on the images according to the detection result of at least one second feature parameter among the feature parameters and the first position information to determine second position information of the user. The at least one second feature parameter is different from the at least one first feature parameter. The second position information represents a position of the user.

Abstract: An image detection method for determining positions of a user. According to the image detection method, a plurality of images of the user are obtained, whether the user moves is determined according to the images, a plurality of feature parameters of the plurality of images are obtained, and a body distribution analysis and a face occlusion analysis are performed to determine the position of the user.

Abstract: An image detection method for selecting a representative image of a user is provided. In the image detection method, a plurality of images of the user are obtained, and a plurality of feature parameters of the plurality of images are obtained. A face occlusion analysis is performed on the plurality of images according to the plurality of feature parameters to determine whether the plurality of images clearly show the user's face. A plurality of feature vectors are determined, and a body distribution analysis is performed on the plurality of images according to the plurality of feature vectors to determine a body position and a position type of the user. An image related to the position type is selected according to results of the face occlusion analysis and the body distribution analysis.