Boyan Technologies (shenzhen) Co., Ltd

Jiawen Gu

Jiangtao Wen

Yuxing Han

Yanghao Li

Yu Zhang

Rui Guo Zhang

Rui Zhang

Minhao Tang

Bichuan Guo

Ziyu Zhu

A video processing method, including: acquiring a plurality of raw videos, the plurality of raw videos being videos acquired by a plurality of dynamic image recorders arranged according to preset locations; determining an overlapping region between every two adjacent raw videos according to preset rules corresponding to the preset locations, the adjacent raw videos being the raw videos acquired by the dynamic image recorders arranged adjacent to each other; performing multi-stage optical flow calculation on the raw videos in each overlapping region to obtain a plurality of pieces of target optical flow information; and splicing the overlapping region of every two adjacent raw videos based on the target optical flow information to obtain target videos.

Optical flow based omnidirectional stereo video processing method

An image processing method, device, storage medium and camera are provided. The method, applied to the camera, comprises: capturing a target image; acquiring a target feature map of the target image through a preset target convolution layer, wherein the target convolution layer includes at least one of a plurality of convolution layers of a convolutional neural network (CNN); and outputting the target feature map. That is to say, after the target image is captured by the camera, the target feature map may be acquired by processing the target image through the target convolution layer pre-integrated in the camera. In this way, the camera transmits the target feature map only to reduce the transmitted data volume, thereby being capable of shortening transmission delay and saving bandwidth required by image transmission.

Image processing method, device, storage medium and camera

A method for tracking target object, storage medium and electronic device, which relate to the field of an image processing technology. The method includes: receiving at least one target image captured by a single photon avalanche diode (SPAD) camera before present moment; for each target image, inputting the target image and a preset template image into a pre-trained siamese network to acquire a position of a target object in the target image output by the siamese network, wherein the template image includes the target object; and determining a position of the target object in an image to be predicted based on the position of the target object in each target image, wherein the image to be predicted is an image captured by the SPAD camera at the present moment.

Method for tracking target object

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Shenzhen, China

Jiawen Gu