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 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: An object positioning system and an object positioning method are provided. The object positioning system includes a sensing device, a storage device and a processing device. The sensing device collects point cloud data obtained from a scene including a target object. The processing device inputs surrounding area data centered on a key point and a preset feature descriptor to a neural network to calculate a scene feature descriptor of the scene. The processing device performs feature matching between the scene feature descriptor and the preset feature descriptor, and calculates a position of the target object in an actual space. The invention utilizes the feature extraction capability of the neural network to effectively improve the accuracy and stability of target object identification and positioning.

Abstract: An image recognition method and an unmanned aerial vehicle system are provided. A training image marked with a specified range is received, and a plurality of features are extracted from the training image through a basic model to obtain a feature map. Next, a frame selection is performed on each point on the feature map to obtain a plurality of initial detection frames, and a plurality of candidate regions are selected in the initial detection frames based on the specified range. Thereafter, the obtained candidate regions are classified to obtain a target block, feature data corresponding to the target block is extracted from the feature map, and a parameter of the basic model is adjusted based on the extracted feature data. In the disclosure, a higher-resolution image is achieved, time flexibility is provided, and accuracy of image recognition is thereby improved.

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: An electronic device and a display method for word information thereof are provided. The display method for word information includes following steps: identifying a user to acquire a user characteristic; acquiring a user word table according to the user characteristic; detecting a selected word pointed by a pointing device; and when the selected word is recorded in the user word table, displaying the word information corresponding to the selected word according to the user word table, wherein the word information includes at least one of word translation and a word note corresponding to the selected word.

Abstract: An adjustable lens assembly includes a lens barrel for carrying a lens, at least one guiding member having a shaft axis parallel to the optical axis of the lens barrel for guiding the direction of motion of the lens barrel, a gear shaft driven by a driving source, a driving member meshing with the gear shaft, and a connection mechanism connecting the lens barrel and the driving member. The connection mechanism is capable of adjusting itself with multiple degrees of freedom so that if there is three-dimensional skew bias between the gear shaft and the optical axis or the guiding member, the lens barrel can be driven smoothly.