Abstract: The present invention discloses a multispectral stereo camera self-calibration algorithm based on track feature registration, and belongs to the field of image processing and computer vision. Optimal matching points are obtained by extracting and matching motion tracks of objects, and external parameters are corrected accordingly. Compared with an ordinary method, the present invention uses the tracks of moving objects as the features required for self-calibration. The advantage of using the tracks is good cross-modal robustness. In addition, direct matching of the tracks also saves the steps of extraction and matching the feature points, thereby achieving the advantages of simple operation and accurate results.

Abstract: The present disclosure relates to an electromagnetic stamping method and an electromagnetic stamping device. The electromagnetic stamping method includes: dividing a blank holder of a stamping device into a plurality of blank holder areas based on a contour characteristic of a workpiece to be stamped; setting a blank holder force function over time for each blank holder area based on a shape characteristic of the blank holder area; collecting blank holder force data of each blank holder area every cycle period t0, and calculating an error between the blank holder force data and a value of the blank holder force function at a current time; and controlling a blank holder force for each blank holder area based on the error, and obtaining the workpiece to be stamped by stamping sheet material under the blank holder force.

Abstract: The invention discloses a deep network lung texture recognition method combined with multi-scale attention, which belongs to the field of image processing and computer vision. In order to accurately recognize the typical texture of diffuse lung disease in computed tomography (CT) images of the lung, a unique attention mechanism module and multi-scale feature fusion module were designed to construct a deep convolutional neural network combing multi-scale and attention, which achieves high-precision automatic recognition of typical textures of diffuse lung diseases. In addition, the proposed network structure is clear, easy to construct, and easy to implement.

Abstract: Embodiments of the present disclosure provide a ferromagnetic object detection device and a method for detecting a tubing coupling. The ferromagnetic object detection device includes a support tube, a magnetic field generating device and a magnetic detection device. The support tube includes a space penetrating in a first direction; the magnetic field generating device is located on an outer sidewall of the support tube and configured to generate a magnetic field; the magnetic field detection device includes a first magnetic field detection element, a second magnetic field detection element and a third magnetic field detection element.

Abstract: The invention discloses an unsupervised content-preserved domain adaptation method for multiple CT lung texture recognition, which belongs to the field of image processing and computer vision. This method enables the deep network model of lung texture recognition trained in advance on one type of CT data (on the source domain), when applied to another CT image (on the target domain), under the premise of only obtaining target domain CT image and not requiring manually label the typical lung texture, the adversarial learning mechanism and the specially designed content consistency network module can be used to fine-tune the deep network model to maintain high performance in lung texture recognition on the target domain. This method not only saves development labor and time costs, but also is easy to implement and has high practicability.

Abstract: An earphone control method is applied to an earphone box provided with a first electrical contact, when the first electrical contact is in a charging state, the first electrical contact is configured for charging the earphone, and when the first electrical contact is a communication state, the first electrical contact is configured for establishing communication between the earphone box and the earphone, the method includes: in responding to that the first electrical contact is in the charging state, and the earphone box detects that a communication requirement exists between the earphone box and the earphone, adjusting a voltage level of the first electrical contact to send preset signals to the earphone; and upon receiving a response signal fed back by the earphone based on the preset signals, switching the first electrical contact to the communication state. An earphone box, an earphone and a computer-readable storage medium are also disclosed.

Abstract: A display panel, a display device, and a method of manufacturing a display panel are provided. As an example, the display panel includes an array layer, a planarization layer, an inorganic layer, and at least one dam. The array layer includes a first region and a second region surrounding the first region. The planarization layer is at least partially located on a portion of the array layer which is at the first region. The inorganic layer is located on a portion of the array layer which is at the second region. The at least one dam is formed on the inorganic layer.

Abstract: A method for controlling heating of a motor includes: obtaining a heating target temperature value; determining, based on the heating target temperature value, a heating motor that needs to generate heat from a plurality of motors of a multi-motor drive system and heat generation power of the heating motor; and sending a first control instruction to the heating motor. The first control instruction is used to respectively input harmonic currents to three phases of windings of the motor, so that the heating motor generates heat based on the heat generation power. In this way the heating target temperature value is obtained. Therefore, the quantity of heating motors can be flexibly controlled to generate sufficient heat generation power.

Abstract: Provided is a combined suction anchor reinforced by a grouting spiral anchor, including a gravity suction anchor, an L-shaped skirt board and a spiral anchor. The gravity suction anchor includes a suction anchor top plate and a wall of a suction anchor barrel body and uses a concrete press block to reach an estimated set position faster during penetration due to self-weight thereof. Thereafter, the skirt board is lifted to outside of the suction anchor through a lug, and a fixing bolt is used to connect the skirt board to the suction anchor. The spiral anchor rod passes through a skirt board hole performed in the skirt board to penetrate into a deep site of seabed, and concrete is grouted through the skirt board hole to a seabed soil area loosened due to penetration of the spiral anchor rod, thereby forming a concrete reinforced area after the concrete solidifies.

Abstract: The present invention discloses a multispectral camera external parameter self-calibration algorithm based on edge features, and belongs to the field of image processing and computer vision. Because a visible light camera and an infrared camera belong to different modes, fewer satisfactory point pairs are obtained by directly extracting and matching feature points. In order to solve the problem, the method starts from the edge features, and finds an optimal corresponding position of an infrared image on a visible light image through edge extraction and matching. In this way, a search range is reduced and the number of the satisfactory matched point pairs is increased, thereby more effectively conducting joint self-calibration on the infrared camera and the visible light camera. The operation is simple and results are accurate.

Abstract: The present invention belongs to the field of image processing and computer vision, and discloses an acceleration method of depth estimation for multiband stereo cameras. In the process of depth estimation, during binocular stereo matching in each band, through compression of matched images, on one hand, disparity equipotential errors caused by binocular image correction can be offset to make the matching more accurate, and on the other hand, calculation overhead is reduced. In addition, before cost aggregation, cost diagrams are transversely compressed and sparsely matched, thereby reducing the calculation overhead again. Disparity diagrams obtained under different modes are fused to obtain all-weather, more complete and more accurate depth information.

Abstract: A disparity image fusion method for multiband stereo cameras belongs to the field of image processing and computer vision. The method obtains pixel disparity confidence information by using the intermediate output of binocular disparity estimation. The confidence information can be used to judge the disparity credibility of the position and assist disparity fusion. The confidence acquisition process makes full use of the intermediate output of calculation, and can be conveniently embedded into the traditional disparity estimation process, with high calculation efficiency and simple and easy operation. In the disparity image fusion method for multiband stereo cameras proposed by the method, the disparity diagrams participating in the fusion are obtained according to the binocular images of the corresponding bands, which makes full use of the information of each band and simultaneously avoiding introducing uncertainty and errors.

Abstract: The present invention discloses a disparity estimation optimization method based on upsampling and exact rematching, which conducts exact rematching within a small range in an optimized network, improves previous upsampling methods such as neighbor interpolation and bilinear interpolation for disparity maps or cost maps, and works out a propagation-based upsampling method by the way of network so that accurate disparity values can be better restored from disparity maps in the upsampling process.

Abstract: The present invention discloses a method for constructing a grid map by using a binocular stereo camera. A high-performance computing platform is constructed by using a binocular camera and a GPU, and a high-performance solving algorithm is constructed to obtain a high-quality grid map containing three-dimensional information. The system in the present invention is easy to construct, so the input data may be collected by using the binocular stereo camera; the program is simple and easy to implement. According to the present invention, the grid height is calculated by using spatial prior information and statistical knowledge, so that a three-dimensional result is more robust; and according to the present invention, the adaptive threshold of grids is solved by using spatial geometry, filtering and screening of the grids are completed, and thus the generalization ability and robustness of the algorithm are improved.

Abstract: The present invention discloses a disparity estimation method for weakly supervised trusted cost propagation, which utilizes a deep learning method to optimize the initial cost obtained by the traditional method. By combining and making full use of respective advantages, the problems of false matching and difficult matching of untextured regions in the traditional method are solved, and the method for weakly supervised trusted cost propagation avoids the problem of data label dependency of the deep learning method.

Abstract: The present invention discloses a grid map obstacle detection method fusing probability and height information, and belongs to the field of image processing and computer vision. A high-performance computing platform is constructed by using a GPU, and a high-performance solving algorithm is constructed to obtain obstacle information in a map. The system is easy to construct, the program is simple, and is easy to implement. The positions of obstacles are acquired in a multi-layer grid map by fusing probability and height information, so the robustness is high and the precision is high.

Abstract: The present invention discloses a disparity estimation method for weakly supervised trusted cost propagation, which utilizes a deep learning method to optimize the initial cost obtained by the traditional method. By combining and making full use of respective advantages, the problems of false matching and difficult matching of untextured regions in the traditional method are solved, and the method for weakly supervised trusted cost propagation avoids the problem of data label dependency of the deep learning method.

Abstract: The present invention discloses a large-field-angle image real-time stitching method based on calibration, and belongs to the field of image processing and computer vision. First, a calibration algorithm is used to solve the positional relationship between cameras, and the prior information is used to solve a homography matrix between images.

Abstract: The present invention discloses a multispectral stereo camera self-calibration algorithm based on track feature registration, and belongs to the field of image processing and computer vision. Optimal matching points are obtained by extracting and matching motion tracks of objects, and external parameters are corrected accordingly. Compared with an ordinary method, the present invention uses the tracks of moving objects as the features required for self-calibration. The advantage of using the tracks is good cross-modal robustness. In addition, direct matching of the tracks also saves the steps of extraction and matching the feature points, thereby achieving the advantages of simple operation and accurate results.