Abstract: The current disclosure relates to a panoramic look-around view generation method, an in-vehicle device and an in-vehicle system.

Abstract: A method of describing a temporal event, including receiving a video sequence of the temporal event, extracting at least one physical characteristic of an at least one occupant within the video sequence, extracting at least one action of the at least one occupant within the video sequence, extracting at least one interaction of the at least one occupant with a secondary occupant within the video sequence, determining a safety level of the temporal event within a vehicle based on at least one of the at least one action and the at least one interaction and describing the at least one physical characteristic of the at least one occupant and at least one of the at least one action and the at least one interaction of the at least one occupant.

Abstract: A time synchronization method, apparatus, domain controller, and storage medium are disclosed. The domain controller is mounted in a vehicle and includes a number of SoCs and micro control units. The SoCs and micro control units are respectively, communicatively connected through the controller area network bus and respectively connected to the switch via Ethernet. The switch has external Ethernet interfaces. A main SoC in the number of SoCs has external UART/PPS interfaces and the micro control units have external FlexRay interfaces. The time synchronization method of the domain controller includes any one of the steps of receiving a time service from an external device through the UART/PPS interfaces, receiving a time service from the external device through the switch over the Ethernet interface, or receiving a time service from the external device through the FlexRay interface under a normal operation phase of the vehicle.

Abstract: A sensor configuration method, an apparatus, computer equipment and a storage medium are disclosed. The method includes acquiring connection configuration information generated based on user input, querying for a target sensor driver matched with a target sensor represented by the sensor identifier in a device driver set, calling a target communication port driver matched with the target communication port represented by the communication port identifier and establishing communications with the target sensor by the target sensor driver and the target communication port driver. The connection configuration information includes a sensor identifier and a communication port identifier. The device driver set is pre-stored with a number of sensor drivers corresponding to a number of sensors.

Abstract: The present disclosure provides a reverse assist method for a vehicle, comprising: transforming an i-th image in a reversing direction acquired by a camera unit at time Ti into an i-th top plan view, wherein i?1; generating an i-th result image based on the i-th top plan view, wherein when i is greater than 1, the i-th top plan view and an intermediate image are spliced to generate an i-th result image; outputting the i-th result image; and wherein the intermediate image is a view transformed from an image of an outside environment in the reversing direction acquired at a time earlier than Ti, and the intermediate image is updated according to a predetermined condition during reversing.

Abstract: An example method of single-exposure multiple-frame image capture, making an HDR video, comprising, capturing a series of frames at an underexposed setting, selecting a reference image from the series of frames, aligning the series of frames to the reference image, merging the series of frames into one frame based on the reference image, indexing the reference image to a next frame in the series of frames, resulting in an indexed reference image, realigning the series of frames to the indexed reference image and remerging the series of frames into a single frame based on the indexed reference image.

Abstract: An anti-shake image processing method, apparatus, electronic device and storage medium are disclosed. The method includes the following steps. A current actual posture of an imaging device at a current shooting moment of capturing an original image of current frame and multiple reference actual postures of the imaging device at multiple shooting moments of capturing the original images of adjacent multiple frames of the original image of the current frame are obtained. A path smoothing process is performed to determine a current virtual posture after path smoothing at the current shooting moment. A coordinate transformation is performed on the original image of the current frame captured in the current actual posture to an estimated position of the original image of the current frame when captured in the current virtual posture in a pixel coordinate system to obtain a first correction image of the current frame.

Abstract: The present application relates to a kernel debugging system and method. The kernel debugging system includes: a user interface module, the user interface module being configured to edit program codes and output an execution result of the program codes; a compilation module, the compilation module being configured to compile the program codes into object files; and a Kwasm engine, the Kwasm engine being directly installed in a system kernel of an operating system, and being configured to interpret and execute the object files in a kernel mode, so as to obtain the execution result of the program codes. On the basis of the kernel debugging system, a user can write program codes like writing a common application program, namely, the program codes can be run and executed in a system kernel without paying attention to details of the system kernel.

Abstract: An extensible multi-precision data pipeline system, comprising, a local buffer that stores an input local data set in a local storage format, an input tensor shaper coupled to the local buffer that reads the input local data set and converts the input local data set into an input tensor data set having a tensor format of vector width N by tensor length L, a cascaded pipeline coupled to the input tensor shaper that routes the input tensor data set through at least one function stage resulting in an output tensor data set, an output tensor shaper coupled to the cascaded pipeline that converts the output tensor data set into an output local data set having the local storage format and wherein the output tensor shaper writes the output local data set to the local buffer.

Abstract: The present invention discloses a system and method for image processing and recognizing a scene of an image. The system utilizes a Multi-mode scalable network system and regrouping pipeline. The system is AI based system which uses neuro network. The system includes a pre-processing, processing and a post-processing unit. The system uses optical information recorded from the camera of a mobile device to extract and analyze the content in an image such as a photo or video clip. Based on the retrieved information, a label is given to best describe the scene of the image.

Abstract: A method of instance segmentation, comprising, defining a bounding box, depth mapping the bounding box, sorting the depth map, estimating stability due to noise of the sorted depth map, detecting low frequency jumps of the sorted depth map based on the estimated stability, detecting high frequency jumps of the sorted depth map, comparing the detected low frequency jumps and the detected high frequency jumps, detecting at least one of a largest object and a closest object based on the comparison and pixel masking the at least one of the largest object and the closest object.

Abstract: An example operation of depth map generation includes one or more of, simultaneously capturing a main-off camera image and an auxiliary-off camera image with an unpowered flash, sparse depth mapping an object based on the main-off camera image and the auxiliary-off camera image, capturing a main-on camera image with a powered flash, foreground probability mapping the object based on the main-off camera image and the main-on camera image and dense depth mapping the object based on the sparse depth map and the foreground probability map.

Abstract: A method of motion control and textured display, comprising, receiving an image, extracting an initial mask of a subject of interest from the image, segmenting the image into the initial mask and a background, determining a color texture of the initial mask, estimating motion of the initial mask to a new mask and merging the new mask and the background into a merged image.

Abstract: The present invention discloses a system for precise representation of object segmentation with multi-modal input for real-time video applications. The multi-modal segmentation system takes advantage of optical, temporal as well as spatial information to enhance the segmentation for AR and VR or other entrainment purpose with accurate details. The system can segment foreground objects such as human and salient objects within a video frame and allows locating object-of-interest for multiple-purposes.

Abstract: The present invention discloses system and method for processing an image. The invention processes the image by segmenting a human portrait region of the image. The invention uses ahierarchical hybrid loss module for masking the portrait region generating masked portrait region. The invention also uses data learning the masked portrait region.

Abstract: A distributed light source couple-able to a mobile device, comprising, a distributed array of light emitting points and a mount connected to the distributed array and couple-able to the mobile device, the distributed array capable of light emission from a plurality of areas.

Abstract: An example method of infrared access, comprising, receiving a plurality of visual images, receiving a plurality of infrared images, calibrating pairs of at least one of the plurality of visual images to a respective at least one of the plurality of infrared images, determining an average temperature of the plurality of infrared images, determining a temperature of the respective calibrated pairs, and granting access if a visual image of the calibrated pair is authenticated by a facial recognition library and if the temperature of the calibrated pair is within a predefined threshold of the average temperature.

Abstract: A method of depth-of-field simulation, including receiving a plurality of images, predicting a layer of interest mask of the plurality of images, determining a plurality of mean brightness anchor values of a respective plurality of layers of interest window arrays, setting a plurality of layers of interest set of binary codes, determining a hamming distance between plurality of layers of interest set of binary codes, determining a cost volume based on the hamming distance, resampling a vertical cost based on a vertical ordinal direction the cost volume, resampling a horizontal cost based on a horizontal ordinal direction the cost volume, determining an all-in-focus layer based on the vertical cost and the horizontal cost, determining an out-of-focus layer based on the vertical cost and the horizontal cost and determining a depth of the all-in-focus layer and out-of-focus layer.

Abstract: A method of auto white balancing, including, receiving an original image, determining an RG logarithmic ratio of a set of red to green channel values of the original image, determining a BG logarithmic ratio of a set of blue to green channel values of the original image, determine an original two-dimensional histogram utilizing the RG logarithmic ratio and the BG logarithmic ratio, determine a Gaussian-blur two-dimensional histogram utilizing the RG logarithmic ratio and the BG logarithmic ratio, determining a sharpened two-dimensional histogram of a sharpened image utilizing the RG logarithmic ratio and the BG logarithmic ratio, determining a Laplacian-edge two-dimensional histogram of a Laplacian-edge image utilizing the RG logarithmic ratio and the BG logarithmic ratio and determining a white balancing gain utilizing a neural network based on the original 2D histogram, the Gaussian-blur 2D histogram, the sharpened 2D histogram and the Laplacian-edge 2D histogram.

Abstract: The present invention discloses system and method for fake face identification. The system is a multi-spectral sensing based bio-security system. The system uses CNN module along with thermal sensors to detect human face and also detects the human temperature. The system authenticates a human face and in case of temperature generates an alarm as an alert.