A method, computer device, and storage medium for exploring and collecting scene reconstruction data. The method includes: capturing a scene image; performing real-time environment perception on the scene image to detect object to be reconstructed in the scene image and reconstructing three-dimensional representation data of the object to be reconstructed; determining a reconstruction target in the object to be reconstructed based on the three-dimensional representation data of the object to be reconstructed and a preset distance threshold; generating an exploration path according to a preset exploration path planning algorithm and exploring an area to be reconstructed according to the exploration path; and collecting reconstruction data of the reconstruction target according to the preset exploration path planning algorithm when the reconstruction target is reached.

An image processing method includes: performing target object detection on an initial image to obtain an object detection result, and performing image saliency detection on the initial image to obtain a saliency detection result; cropping the initial image based on the object detection result and the saliency detection result to obtain a corresponding cropped image; acquiring an image template for indicating an image style, and acquiring layer information corresponding to the image template; and adding the layer information to the cropped image based on the image template to obtain a target image corresponding to the image style indicated by the image template.

An electronic device for smoke estimation is provided. The electronic device receives a first image of a plurality of images of a physical space. The electronic device detects smoke in the physical space based on an application of a trained neural network model on the received first image. The electronic device generates a heatmap of the physical space based on the detected smoke in the physical space, and further based on an output of the trained neural network model corresponding to the detection of the smoke. The electronic device estimates a level of the smoke in the physical space based on a normalization of the generated heatmap.

A system that measures the motion of a platform traveling over water by reference to images taken from the platform. In one embodiment, the invention is comprised of a computer connected to a camera and an Inertial Measurement Unit (IMU) which provides estimates of the platform's location, attitude and velocity by integrating the motion of the platform with respect to features on the water's surface, corrected for the motion of those features. The invention measures the motion of the water features according to equations of surface water wave celerity to measure motion of features across the water, and by measuring the feature motion shear across images or the discrepancy between the navigation estimates and the observed water feature motion to detect boundaries of water currents. The invention is also capable of measuring water depth, wave motion, sea state and current present in the water, whether affixed to a navigating platform or to a stationary reference point.

Systems and techniques are described for performing object detection and tracking. For example, a tracking object can obtain an image comprising a target object at least partially in contact with a surface. The tracking object can obtain a plurality of two-dimensional (2D) keypoints based on one or more features associated with one or more portions of the target object in contact with the surface in the image. The tracking object can obtain information associated with a contour of the surface. Based on the plurality of 2D keypoints and the information associated with the contour of the surface, the tracking object can determine a three-dimensional (3D) representation associated with the plurality of 2D keypoints.

A method and a device for 3D shape matching based on a local reference frame are proposed. After acquiring a 3D point cloud and feature points in the method, the feature point set is projected to a plane, and feature transformation is performed on the projected points by using at least one factor from the distances between the 3D points and the feature points, the distances between the 3D points and the projected points, and the average distances between the 3D points and its 1-ring neighboring points to acquire a point distribution with a larger variance in a certain direction than the projected point set, and the local reference frame is determined based on the transformed point distribution. The 3D local feature descriptor established based on this local reference frame can encode the 3D local surface information more robustly, so as to obtain a better 3D shape matching effect.

The invention relates to a method for automated calibration of sensors of a vehicle, wherein at least one first passive optical sensor and at least one second active optical sensor are calibrated by a calibration unit based on a matching spatial orientation of recognised environmental features in transformed sensor data of the first sensor and the sensor data captured by the second sensor.

A method and apparatus for positioning a key point, a device, and a storage medium are provided. The method may include: extracting a first feature map and a second feature map of a to-be-positioned image, the first feature map and the second feature map being different feature maps; determining, based on the first feature map, an initial position of a key point in the to-be-positioned image; determining, based on the second feature map, an offset of the key point; and adding the initial position of the key point with the offset of the key point to obtain a final position of the key point.

Disclosed are methods, systems, and computer-readable medium for obstacle detection and database management using multi-source weightages. For instance, the method may include: responsive to a detection of an object, determining whether the object is a known object or an unknown object based on object features and known objects indicated by vehicle state information and an obstacle database; responsive to a determination that the object is an unknown object, updating the obstacle database with unknown object information and transmitting the unknown object information to an off-board service; receiving a response from the off-board service, the response including a weightage assigned to the unknown object; updating the obstacle database with the weightage assigned to the unknown object; and performing at least one action based on the weightage of the unknown object.

A set of POIs of a point cloud are received at a first filter, where each POI of the set of POIs comprises one or more points. Each POI of the set of POIs is filtered. A set of neighborhood points of a POI is selected. A metric for the set of neighborhood points is computed. Based on the metric, whether to accept the POI, modify the POI, reject the POI, or transmit the POI to a second filter, to extract at least one of range or velocity information related to the target is determined. Provided the POI is accepted or modified, the POI is transmitted to a filtered point cloud; provided the POI is rejected, the POI is prevented from reaching the filtered point cloud; provided the POI is not accepted, modified, or rejected, the POI is transmitted to a second filter.