Abstract: A UAV (Unmanned Aerial Vehicle) control method comprises: obtaining a first image; obtaining a second image after obtaining the first image; calculating a plurality of feature points respectively according to the first image and the second image by a computing device, extracting a first feature point set and a second feature point set by the computing device; calculating a first-axial displacement and a second-axial displacement according to the first feature point set and the second feature point set by the computing device; calculating a first ROI (Region Of Interest) area, a second ROI and a third-axial displacement according to the first feature point set and the second feature point set by the computing device; adjusting a camera pose or a flight path of the UAV according to the first-axial displacement, the second-axial displacement and the third-axial displacement.

Abstract: A UAV (Unmanned Aerial Vehicle) control method comprises: obtaining a first image; obtaining a second image after obtaining the first image; calculating a plurality of feature points respectively according to the first image and the second image by a computing device, extracting a first feature point set and a second feature point set by the computing device; calculating a first-axial displacement and a second-axial displacement according to the first feature point set and the second feature point set by the computing device; calculating a first ROI (Region Of Interest) area, a second ROI and a third-axial displacement according to the first feature point set and the second feature point set by the computing device; adjusting a camera pose or a flight path of the UAV according to the first-axial displacement, the second-axial displacement and the third-axial displacement.

Abstract: A video indexing method includes: analyzing trajectory information of a plurality of objects in video data and storing a plurality of pieces of object trajectory data obtained correspondingly in a storage device; determining whether the storage device satisfies a data removal condition; when the data removal condition is satisfied, performing an object trajectory analysis on the plurality of pieces of object trajectory data to select at least one target object from the objects; and extracting the object trajectory data of the at least one target object from the storage device and generating at least one video indexing image accordingly.

Abstract: The present disclosure provides a method for generating a video frame and a system thereof, including: receiving at least two frames of a video captured by an image capture unit through a network; calculating a first set of optical flow vectors of the at least two frames by a first algorithm; generating a set of modified vectors according to at least one parameter; combining the set of modified vectors and the first set of optical flow vectors to obtain a second set of optical flow vectors; and shifting one of the at least two frames according to the second set of optical flow vectors to generate a virtual image. Therefore, the present disclosure can reduce deviation caused by the latency of the network and improve user experience.

Abstract: The present disclosure provides a method for generating a video frame and a system thereof, including: receiving at least two frames of a video captured by an image capture unit through a network; calculating a first set of optical flow vectors of the at least two frames by a first algorithm; generating a set of modified vectors according to at least one parameter; combining the set of modified vectors and the first set of optical flow vectors to obtain a second set of optical flow vectors; and shifting one of the at least two frames according to the second set of optical flow vectors to generate a virtual image. Therefore, the present disclosure can reduce deviation caused by the latency of the network and improve user experience.

Abstract: A video indexing method includes: analyzing trajectory information of a plurality of objects in video data and storing a plurality of pieces of object trajectory data obtained correspondingly in a storage device; determining whether the storage device satisfies a data removal condition; when the data removal condition is satisfied, performing an object trajectory analysis on the plurality of pieces of object trajectory data to select at least one target object from the objects; and extracting the object trajectory data of the at least one target object from the storage device and generating at least one video indexing image accordingly.

Abstract: A video indexing method is provided. The video indexing method includes steps of: analyzing trajectory information of a plurality of objects in a video data to obtain a sequence of object snaps including a plurality of object snaps; generating a sequence of candidate object snaps by filtering off some of the object snaps according to the appearance differences between the object snaps; selecting a plurality of representative object snaps from the sequence of candidate object snaps; and generating a video indexing image by merging the selected representative object snaps into a background image.

Abstract: According to one exemplary embodiment, a method for image processing selects at least one image from a plurality of images, and stores the plurality of images into a buffer, until a storage space of the buffer reaches a criterion. When the storage space of the buffer reaches the criterion, a procedure of image processing is performed for a plurality of temporary images stored in the buffer, which includes constructing an image dictionary according to the at least an image selected, and performing an image recovery and reconstruction procedure for the plurality of temporary images in the buffer according to the image dictionary, thereby obtaining a plurality of reconstructed images.

Abstract: An image processing device for reducing image noise and the method thereof are provided. The method for reducing image noise includes the following steps. A filtering operation is performed on a plurality of pixel values of a first image according to a high-pass (HP) filtering mask, a first default filtering mask and a second default filtering mask to obtain a high-pass filtering image, a first low-pass (LP) image and a second LP image, respectively. A difference between the first and the second LP images is calculated to obtain a LP difference image. A pixel weighting calculation is performed according to the HP image and the LP difference image to obtain a pixel weighting mask corresponding to the first image. The first image is calculated according to the pixel weighting mask and one of the first and the second LP images to obtain a noise reducing image.

Abstract: According to one exemplary embodiment, a method for image processing selects at least one image from a plurality of images, and stores the plurality of images into a buffer, until a storage space of the buffer reaches a criterion. When the storage space of the buffer reaches the criterion, a procedure of image processing is performed for a plurality of temporary images stored in the buffer, which includes constructing an image dictionary according to the at least an image selected, and performing an image recovery and reconstruction procedure for the plurality of temporary images in the buffer according to the image dictionary, thereby obtaining a plurality of reconstructed images.

Abstract: An image processing device for reducing image noise and the method thereof are provided. The method for reducing image noise includes the following steps. A filtering operation is performed on a plurality of pixel values of a first image according to a high-pass (HP) filtering mask, a first default filtering mask and a second default filtering mask to obtain a high-pass filtering image, a first low-pass (LP) image and a second LP image, respectively. A difference between the first and the second LP images is calculated to obtain a LP difference image. A pixel weighting calculation is performed according to the HP image and the LP difference image to obtain a pixel weighting mask corresponding to the first image. The first image is calculated according to the pixel weighting mask and one of the first and the second LP images to obtain a noise reducing image.

Abstract: A physiological information measurement system includes at least one video capture unit, a calculating unit electrical coupled to the video capture unit and a display unit electrical coupled to the calculating unit. The video capture unit captures at least one video provided to the calculating unit. The calculating unit measures physiological information according to the video. The display unit shows the physiological information.

Abstract: A video analytics based object counting method which can obtain and process video frames from one or more video sources is proposed. By setting a variety of parameters, calculating a reference point, and a mapping table, a sampled referenced image can be constructed to obtain image pixels variation information according to these parameters. With the changed value of multiple sampling line segments and the pre-defined reference object, total object counts can be estimated by analyzing the whole number of the triggered sampling line segments and their directional states.

Abstract: A video analytics based object counting method which can obtain and process video frames from one or more video sources is proposed. By setting a variety of parameters, calculating a reference point, and a mapping table, a sampled referenced image can be constructed to obtain image pixels variation information according to these parameters. With the changed value of multiple sampling line segments and the pre-defined reference object, total object counts can be estimated by analyzing the whole number of the triggered sampling line segments and their directional states.

Abstract: A method and a system for heart rate measurement are provided. The method includes: capturing at least one image, detecting skin-like points by using a skin color detector, labeling the skin-like points and tracking at least one target to be measured, taking statistics on color values of the target at multiple time points, measuring the heart rate through frequency transformation. The method and the system are easy to setup fully an automatic contact-free measurement of multiple persons' heart rates at a time, and applicable in multiple regions of human body for heart rate measurement such as head and neck, arm, and palm regions.