Abstract: The topographic environment detection method and a topographic environment detection system based on a binocular stereo camera, and an intelligent terminal are provided. The topographic environment detection method includes: obtaining a left-eye image and a right-eye image about a same road scenario, and processing the left-eye image and the right-eye image to obtain a dense disparity map of the road scenario; converting image information in a detection region into 3D point cloud information in a world coordinate system in accordance with the dense disparity map; fitting a road surface model in accordance with the 3D point cloud information; inputting an image in the detection region into a trained semantic segmentation model, and obtaining a segmentation result from the semantic segmentation model; and obtaining topographic information about the detection region in accordance with the segmentation result, and transmitting the topographic information to a vehicle assistant driving system.

Abstract: The present disclosure provides a vehicle positioning device for vehicle vision calibration, a positioning adjustment method, and a positioning adjustment system. The vehicle positioning device includes a base, a chassis, a translation mechanism and a rotation mechanism. A to-be-calibrated vehicle is placed onto the chassis, and the chassis is provided with a stopper. The translation mechanism is arranged between the chassis and the base, and configured to drive the chassis to move in an X-axis direction in a three-dimensional coordinate system relative to the base in accordance with a translation control instruction. The rotation mechanism is arranged between the chassis and the base, and configured to drive the chassis to rotate about a Z-axis in the three-dimensional coordinate system relative to the base in accordance with a rotation control instruction.

Abstract: A time threshold model creation method and a time threshold model creation system based on an autonomous braking system are provided. The method includes the steps of: obtaining braking data about a target vehicle; creating a three-dimensional space in accordance with a braking time, a speed of the target vehicle, and a relative speed, and obtaining a point cloud of the braking data in the three-dimensional space; dividing a two-dimensional plane defined by the speed of the target vehicle and the relative speed into a plurality of statistical regions, and calculating a probability in each statistical region to obtain a fitted probability distribution curve; calculating a time threshold in each statistical region in accordance with the fitted probability distribution curve; and obtaining a target curve surface of the time thresholds in accordance with the distribution of the time threshold in each statistical region in the three-dimensional space.

Abstract: An RGB-D fusion information-based obstacle target classification method includes: collecting an original image through a binocular camera within a target range, and acquiring a disparity map of the original image; collecting a color-calibrated RGB image through a reference camera of the binocular camera within the target range; acquiring an obstacle target through disparity clustering in accordance with the disparity map and the color-calibrated RGB image, and acquiring a target disparity map and a target RGB image of the obstacle target; calculating depth information about the obstacle target in accordance with the target disparity map; and acquiring a classification result of the obstacle target through RGB-D channel information fusion in accordance with the depth information and the target RGB image.

Abstract: A method and a system for calculating a focusing parameter of a binocular stereo camera, and an intelligent terminal are provided. The method includes: calculating a lower limit value and an upper limit value of a distance measurement range; acquiring a depth-of-field range in accordance with the lower limit value and the upper limit value; calculating a maximum value and a minimum value of an image distance gain corresponding to a real object distance within the depth-of-field range, and calculating an optimal image distance gain in accordance with the maximum value and the minimum value; acquiring an optimal object distance of a focused target in accordance with the optimal image distance gain; and calculating an optimal size of the focused target in accordance with the optimal object distance.

Abstract: A vehicle braking and warning method includes: acquiring first target information within a detection range of the binocular stereo camera, second target information within a detection range of a millimeter-wave radar, and current vehicle driving information; acquiring sensing result data about a target obstacle in accordance with the first target information and the second target information in conjunction with a predetermined weight; and outputting a braking instruction and/or a warning instruction in accordance with the sensing result data and the current vehicle driving information so as to enable a vehicle to adjust its driving state in accordance with the instructions.

Abstract: A method for automatically braking a commercial vehicle includes: providing a plurality of ultrasonic radars on a front vehicle body of a target commercial vehicle, the ultrasonic radars being configured to detect a region before the target commercial vehicle in a gapless manner, an active speed range being set for each ultrasonic radar; acquiring a current speed of the target commercial vehicle in real time and calculating a safe distance for each ultrasonic radar in accordance with the current speed; and detecting whether there is an obstacle within the safe distance in real time, and when there is the obstacle within the safe distance, transmitting a decelerating or braking instruction to an execution system of the target commercial vehicle.

Abstract: The present disclosure discloses a task processing method and a distributed computing framework. A specific embodiment of the method includes: parsing an expression corresponding to a distributed computing task, and constructing task description information corresponding to the distributed computing task, the task description information being used to describe a corresponding relationship between an operator and a distributed dataset, and the operator acting on at least one of the distributed dataset or distributed datasets obtained by grouping the distributed dataset; determining, based on the task description information, a distributed dataset the operator acting on; and performing distributed computing on the distributed dataset the operator acting on using the operator. In the distributed computing, the acting scope and nesting relationship of the operator is described by constructing a topology.

Abstract: A method and a system for extracting a dense disparity map based on multi-sensor fusion are provided. The method includes: obtaining a left-eye image and a right-eye image in a same road scenario, and point cloud information about the road scenario; generating an initial cost volume map set in accordance with the left-eye image, the right-eye image and the point cloud information; performing multidirectional cost aggregation in accordance with the point cloud information and the initial cost volume map set, and creating an energy function in accordance with the cost aggregation; and solving an optimum disparity for each pixel in the left-eye image in accordance with the energy function, so as to generate the dense disparity map.

Abstract: A real-time ground fusion system is based on binocular stereo vision and an intelligent terminal. The method for accomplish real-time ground fusion includes: S1 of obtaining a disparity map about a same road scenario, and converting a disparity map in a target region into a 3D point cloud; S2 of performing pose conversion on a current frame and a next frame adjacent to the current frame, and performing inverse conversion on a 3D point cloud of the current frame; and S3 of repeating S2 with each frame in the target region as the current frame, so as to achieve ground fusion. Through the conversion and fusion of adjacent frames, holes caused by the projection of the disparity map can be filled to assist driving and output accurate height data, thereby improving comfortableness.

Abstract: The topographic environment detection method and a topographic environment detection system based on a binocular stereo camera, and an intelligent terminal are provided. The topographic environment detection method includes: obtaining a left-eye image and a right-eye image about a same road scenario, and processing the left-eye image and the right-eye image to obtain a dense disparity map of the road scenario; converting image information in a detection region into 3D point cloud information in a world coordinate system in accordance with the dense disparity map; fitting a road surface model in accordance with the 3D point cloud information; inputting an image in the detection region into a trained semantic segmentation model, and obtaining a segmentation result from the semantic segmentation model; and obtaining topographic information about the detection region in accordance with the segmentation result, and transmitting the topographic information to a vehicle assistant driving system.

Abstract: In accordance with one implementation of the present disclosure, a new approach for determining a movement orientation of a user is proposed in indoor navigation. Generally speaking, a device orientation of a terminal device is obtained based on at least one signal stream collected from the terminal device carried by a moving user. A deviation degree is determined based on the at least one signal stream, here the deviation degree represents a deviation between a movement orientation of the user and an actual device orientation of the terminal device. The movement orientation is determined based on the device orientation in accordance with a determination that the deviation degree is below a threshold degree. With the above implementation, the movement orientation of the user is determined in a more effective an accurate way, and thus accuracy of the indoor navigation is increased.

Abstract: In accordance with one implementation of the present disclosure, a new approach for identifying a stepping event is proposed in indoor navigation. Generally speaking, a first signal fragment and a second signal fragment respectively within a first time window and a second time window in an acceleration signal stream are obtained, here the acceleration signal stream is collected from an acceleration sensor associated with a moving user, the first time window being shorter than the second time window. A first amplitude feature and a second amplitude feature are determined for the first and second time windows based on the first and second signal fragments, respectively. A stepping event of the user is identified based on a deviation between the first and second amplitude features. With the above implementation, the stepping event is identified in a more effective an accurate way, and thus accuracy of the indoor navigation is increased.

Abstract: A method and a system for calculating a focusing parameter of a binocular stereo camera, and an intelligent terminal are provided. The method includes: calculating a lower limit value and an upper limit value of a distance measurement range; acquiring a depth-of-field range in accordance with the lower limit value and the upper limit value; calculating a maximum value and a minimum value of an image distance gain corresponding to a real object distance within the depth-of-field range, and calculating an optimal image distance gain in accordance with the maximum value and the minimum value; acquiring an optimal object distance of a focused target in accordance with the optimal image distance gain; and calculating an optimal size of the focused target in accordance with the optimal object distance.

Abstract: A method for automatically braking a commercial vehicle includes: providing a plurality of ultrasonic radars on a front vehicle body of a target commercial vehicle, the ultrasonic radars being configured to detect a region before the target commercial vehicle in a gapless manner, an active speed range being set for each ultrasonic radar; acquiring a current speed of the target commercial vehicle in real time and calculating a safe distance for each ultrasonic radar in accordance with the current speed; and detecting whether there is an obstacle within the safe distance in real time, and when there is the obstacle within the safe distance, transmitting a decelerating or braking instruction to an execution system of the target commercial vehicle.

Abstract: Embodiments of the disclosure provide systems and methods for domain adaptation between a plurality of source domains and a target domain. The artificial intelligence method includes receiving labeled data from the plurality of source domains and unlabeled data from the target domain. The method further includes separately training, by a processor, a plurality of source classifiers each corresponding to a source domain using the labeled data received from the respective source domains. The method also includes selecting a subset of the labeled data received from each source domain based on a similarity between the selected labeled data and the unlabeled data of the target domain. The method additionally includes refining, by the processor, each source classifier using the selected subset of the labeled data, and predicting labels of the unlabeled data using the refined source classifiers.

Abstract: The embodiments of the present disclosure provide a visual positioning method, the method may include obtaining a positioning image collected by an imaging device; obtaining a three-dimensional (3D) point cloud map associated with an area where the imaging device is located; determining a target area associated with the positioning image from the 3D point cloud map based on the positioning image; and determining positioning information of the imaging device based on the positioning image and the target area.

Abstract: An RGB-D fusion information-based obstacle target classification method includes: collecting an original image through a binocular camera within a target range, and acquiring a disparity map of the original image; collecting a color-calibrated RGB image through a reference camera of the binocular camera within the target range; acquiring an obstacle target through disparity clustering in accordance with the disparity map and the color-calibrated RGB image, and acquiring a target disparity map and a target RGB image of the obstacle target; calculating depth information about the obstacle target in accordance with the target disparity map; and acquiring a classification result of the obstacle target through RGB-D channel information fusion in accordance with the depth information and the target RGB image.

Abstract: A method and apparatus for executing a distributed computing task are provided. The method can include: parsing an expression of the distributed computing task to obtain an operator keyword; and executing, by using an operator corresponding to the operator keyword, the distributed computing task based on an input parameter of the operator, the input parameter of the operator including at least one of: a distributed stored distributed dataset including at least one data element, a distributed stored distributed key-value pair set including at least one key-value pair, and a value of the key-value pair in the distributed key-value pair set being a distributed dataset or a distributed key-value pair set.

Abstract: Embodiments of the present disclosure disclose a method and apparatus for recommending a video. A specific implementation of the method includes: finding a recommended video corresponding to a target video from all candidate videos based on similarities of content characteristics of the videos, the target video being a video to be played on a terminal of a user; and sending play information of the recommended video corresponding to the target video to the terminal of the user. The method finds a video similar on video content to the target video that the user desires to view based on the content characteristic of the video, and recommends the video similar on video content to the target video that the user desires to view to the user.