Abstract: An automated moving vehicle and a control method thereof. The control method includes: obtaining a static point cloud and a current point cloud on a work space through a sensor, wherein the current point cloud includes a current scan point; calculating a shortest distance between the current scan point and the static point cloud; in response to the shortest distance being greater than or equal to a first threshold, calculating a first distance between the current scan point and the automated moving vehicle; and in response to the first distance being less than a second threshold, controlling a driving device of the automated moving vehicle to stop a movement of the automated moving vehicle.

Abstract: A method and a system for spatial static map construction are provided. In the method, a three-dimensional space is scanned by using a LiDAR sensor to generate a LiDAR frame including multiple points in the three-dimensional space in a time sequence. As for each point in the LiDAR frame, a corresponding point closest to the point is found from a static map built according to the three-dimensional space, and a distance from the corresponding point is calculated. The point is labelled as a dynamic point if the distance is greater than a threshold, and otherwise labelled as a static point. Each labelled dynamic point is compared with points in N LiDAR frames generated before the time sequence, and corrected as a static point if included in the N LiDAR frames. The dynamic points in the LiDAR frame are removed, and each static point is updated to the static map.

Abstract: The invention provides a projector calibration method for forming a spherical target image at a viewing point. The projector calibration method includes the following steps. A first preset image is projected by a first projector to a dome screen, and a first deformed image is obtained by capturing an image of the dome screen using a first camera. A spatial relationship between the first projector, the first camera, and the dome screen is calculated according to the first preset image and the first deformed image. A first prewarp image is generated according to a target image, a spatial relationship between the first projector and the dome screen, and a spatial relationship between the dome screen and the viewing point. Projection is performed by the first projector according to the first prewarp image. In addition, a projection system using the method is also provided.

Abstract: The disclosure provides a calibration system, a calibration method, and a calibration device. The calibration method for obtaining a transformation of coordinate systems between a vision sensor and a depth sensor includes the following steps. (a) A first coordinate group of four endpoints of a calibration board in a world coordinate system is created. (b) An image of the calibration board is obtained by the vision sensor, and a second coordinate group of the four endpoints of the calibration board in a two-dimensional coordinate system is created. (c) A third coordinate group of the four endpoints of the calibration board in a three-dimensional coordinate system is created according to the first and second coordinate groups. (d) The third coordinate group is transformed to a fourth coordinate group corresponding to the depth sensor to obtain the transformation of the coordinate systems according to at least three target scanning spots.

Abstract: The embodiments of the present invention propose a map construction device and method thereof. According to the method, a three-dimensional map is obtained, the three-dimensional map is converted to an initial two-dimensional map, the occupancy probabilities of the grids on the initial two-dimensional map is determined by the training model, and a final two-dimensional map is generated according to the occupancy probabilities of the grid. The three-dimensional map is constructed based on the depth data generated the architectural space scanning. The initial two-dimensional map is divided into multiple grids. The occupancy probability of each grid is related to whether there is an object occupying thereon. The final two-dimensional map is divided according to the grids, and the grids on the final two-dimensional map are determined whether there are objects occupying thereon. Therefore, according to the map construction device and method of the disclosure, a high-precision two-dimensional map can be generated.

Abstract: A projection system and an image uniformity compensation method thereof are provided. The method includes the following steps. A test image is projected onto a projection surface by a projection device. When the test image is projected, a plurality of color measurement devices is used to perform measurement on the projection surface to acquire a plurality of test color data corresponding to a plurality of measurement positions respectively. An estimated image is established by using the plurality of test color data. Uniformity compensation information of each pixel is updated according to a target value and each piece of pixel information of the estimated image. An initial image is compensated according to the uniformity compensation information to generate a uniformized image, which is then projected by the projection device.

Abstract: A projection device including a processor circuit is provided. The processor circuit generates multiple warped feature points according to multiple first feature points and multiple second feature points. The processor circuit transforms a first mapping table into a second mapping table according to the warped feature points. The projection device projects a correction pattern to a projection screen. The correction pattern includes the first feature points. The processor circuit receives an image of the correction pattern projected to the projection screen that is captured by a 3D image capturing device, so as to obtain coordinate positions of the second feature points. The processor circuit calculates a viewer position according to the coordinate positions of the second feature points. The processor circuit generates an antiwarp image according to an input image and the second mapping table. The projection device projects the antiwarp image to the projection screen.

Abstract: A method and a system for inspecting a display image are provided. A test image is displayed on a display surface through a display device. An optical inspection image is generated by photographing the test image on the display surface by an image capturing device. A brightness channel image and a color channel image of the optical inspection image are obtained by performing color space transformation on the optical inspection image. Background estimation is applied to the color channel image to obtain a color channel background image. At least one color nonuniformity region in the test image is obtained by respectively comparing an inspection reference value with multiple color component pixel values of the color channel background image.

Abstract: The disclosure provides a calibration system, a calibration method, and a calibration device. The calibration method for obtaining a transformation of coordinate systems between a vision sensor and a depth sensor includes the following steps. (a) A first coordinate group of four endpoints of a calibration board in a world coordinate system is created. (b) An image of the calibration board is obtained by the vision sensor, and a second coordinate group of the four endpoints of the calibration board in a two-dimensional coordinate system is created. (c) A third coordinate group of the four endpoints of the calibration board in a three-dimensional coordinate system is created according to the first and second coordinate groups. (d) The third coordinate group is transformed to a fourth coordinate group corresponding to the depth sensor to obtain the transformation of the coordinate systems according to at least three target scanning spots.

Abstract: A method and a system for inspecting a display image are provided. A test image is displayed on a display surface through a display device. An optical inspection image is generated by photographing the test image on the display surface by an image capturing device. A brightness channel image and a color channel image of the optical inspection image are obtained by performing color space transformation on the optical inspection image. Background estimation is applied to the color channel image to obtain a color channel background image. At least one color nonuniformity region in the test image is obtained by respectively comparing an inspection reference value with multiple color component pixel values of the color channel background image.

Abstract: A projection system and an image uniformity compensation method thereof are provided. The method includes the following steps. A test image is projected onto a projection surface by a projection device. When the test image is projected, a plurality of color measurement devices is used to perform measurement on the projection surface to acquire a plurality of test color data corresponding to a plurality of measurement positions respectively. An estimated image is established by using the plurality of test color data. Uniformity compensation information of each pixel is updated according to a target value and each piece of pixel information of the estimated image. An initial image is compensated according to the uniformity compensation information to generate a uniformized image, which is then projected by the projection device.

Abstract: A projection device including a processor circuit is provided. A reverse-warped image is generated by the processor circuit according to an input image and a second mapping table. The projection device is adapted to project the reverse-warped image onto the projection screen. The second mapping table is converted from a first mapping table according to a plurality of warped feature points caused according to a first calibration pattern and a second calibration pattern. A projection system and an image calibration method are also provided. Therefore, an undistorted and a non-warped image may be formed on a curved projection screen and be viewed by a viewer.

Abstract: A projection device including a processor circuit is provided. A reverse-warped image is generated by the processor circuit according to an input image and a second mapping table. The projection device is adapted to project the reverse-warped image onto the projection screen. The second mapping table is converted from a first mapping table according to a plurality of warped feature points caused according to a first calibration pattern and a second calibration pattern. A projection system and an image calibration method are also provided. Therefore, an undistorted and a non-warped image may be formed on a curved projection screen and be viewed by a viewer.

Abstract: A projection device including a processor circuit is provided. The processor circuit generates multiple warped feature points according to multiple first feature points and multiple second feature points. The processor circuit transforms a first mapping table into a second mapping table according to the warped feature points. The projection device projects a correction pattern to a projection screen. The correction pattern includes the first feature points. The processor circuit receives an image of the correction pattern projected to the projection screen that is captured by a 3D image capturing device, so as to obtain coordinate positions of the second feature points. The processor circuit calculates a viewer position according to the coordinate positions of the second feature points. The processor circuit generates an antiwarp image according to an input image and the second mapping table. The projection device projects the antiwarp image to the projection screen.

Abstract: The invention provides a projector calibration method for forming a spherical target image at a viewing point. The projector calibration method includes the following steps. A first preset image is projected by a first projector to a dome screen, and a first deformed image is obtained by capturing an image of the dome screen using a first camera. A spatial relationship between the first projector, the first camera, and the dome screen is calculated according to the first preset image and the first deformed image. A first prewarp image is generated according to a target image, a spatial relationship between the first projector and the dome screen, and a spatial relationship between the dome screen and the viewing point. Projection is performed by the first projector according to the first prewarp image. In addition, a projection system using the method is also provided.

Abstract: A forward and backward image resizing method is used for resizing a low-resolution image into a high-resolution image. In the method, the low-resolution image is obtained first, and then a forward and backward image resizing process is performed, so as to resize the low-resolution image into the high-resolution image with an integral multiple resolution. The forward and backward image resizing process includes: resizing the low-resolution image by the integral multiple, so as to generate a first-resizing image with the integral multiple resolution; further increasing the resolution of the first-resizing image by 2-fold, so as to generate a second-resizing image; and reducing the resolution of the second-resizing image by 2-fold, thereby obtaining the high-resolution image.

Abstract: A method for moving object detection includes the steps: obtaining successive images of the moving object and dividing the successive images into blocks; selecting one block, calculating color feature values of the block at a current time point and a following time point; according to the color feature values, obtaining an active part of the selected block; comparing the color feature value of the selected block at the current time point with that of the other blocks at the following time point to obtain a similarity relating to each of the other blocks, and defining a maximum similarity as a local correlation part; obtaining a motion-energy patch of the block according to the active part and the local correlation part; repeating the steps to obtain all motion-energy patches to form a motion-energy map; and acquiring the moving object at the current time point in the motion-energy map.

Abstract: A method for moving object detection includes the steps: obtaining successive images of the moving object and dividing the successive images into blocks; selecting one block, calculating color feature values of the block at a current time point and a following time point; according to the color feature values, obtaining an active part of the selected block; comparing the color feature value of the selected block at the current time point with that of the other blocks at the following time point to obtain a similarity relating to each of the other blocks, and defining a maximum similarity as a local correlation part; obtaining a motion-energy patch of the block according to the active part and the local correlation part; repeating the steps to obtain all motion-energy patches to form a motion-energy map; and acquiring the moving object at the current time point in the motion-energy map.

Abstract: A forward and backward image resizing method is used for resizing a low-resolution image into a high-resolution image. In the method, the low-resolution image is obtained first, and then a forward and backward image resizing process is performed, so as to resize the low-resolution image into the high-resolution image with an integral multiple resolution. The forward and backward image resizing process includes: resizing the low-resolution image by the integral multiple, so as to generate a first-resizing image with the integral multiple resolution; further increasing the resolution of the first-resizing image by 2-fold, so as to generate a second-resizing image; and reducing the resolution of the second-resizing image by 2-fold, thereby obtaining the high-resolution image.

Abstract: This invention discloses a method and system for counting the number of people. First, a first face information is stored in a memory. Then, an image is determined to be a complexion region or not. The complexion region is determined to be a real face or not. Next, a one-to-one similarity matching is processed between the potential face information and the first face information, when the similarity matching achieves a predetermined condition, use the potential face information to update the first face information, when the similarity matching does not achieve a predetermined condition and the potential face is the real face, the potential face is viewed as a second face information and added to the memory, and the first face information is set as been occluded. Finally, the number of people in front of the camera is counted according to the faces stored in the memory.