Zhejiang Dahua Technology Co., Ltd.

Huadong Pan

Jun Yin

He Sun

Xingming Zhang

Shizhu Pan

Miao Cheng

Chengzhe Meng

Li Sun

Hui Su

Yongtao Yang

Jia Zheng

Jianguo Tian

Mei Gao

Bangjie Tang

Libo Sun

Shixian Luo

The present disclosure relates to systems and methods for object recognition. The systems may obtain an image associated with an object. The systems may determine, using a recognition model, an initial recognition result of the object based on the image. The initial recognition result may include a plurality of initial recognition values corresponding to a plurality of predetermined categories respectively. Each of the plurality of initial recognition values may indicate an initial probability that the object corresponds to a corresponding predetermined category. In response to determining that the initial recognition result satisfies a preset condition, for each of the plurality of predetermined categories, the systems may obtain a reference probability corresponding to the predetermined category. The systems may determine a target recognition result of the object by adjusting the plurality of initial recognition values based on a plurality of reference probabilities corresponding to the plurality of predetermined categories respectively. The target recognition result may include a plurality of target recognition values corresponding to the plurality of predetermined categories respectively. Each of the plurality of target recognition values may indicate a target probability that the object corresponds to a corresponding predetermined category.

Systems and methods for object recognition

A device for transferring micro-components and a method of manufacturing the device are provided. The device includes a substrate, a metal wire, and a plurality of silicon electrodes. The metal wire is formed on a flat surface of the substrate and includes a plurality of electrode driving units. The silicon electrodes are formed on a side of the metal wire opposing to the substrate. Each silicon electrode corresponds to each electrode driving unit and is driven by the electrode driving unit to pick or release each micro-component. According to the present application, the device may electrostatically adsorb a massive amount of micro-components to achieve transferring the massive amount of the micro-components, dramatically improving a transfer efficiency.

Target re-identification method, network training method thereof, and related device

An image capture method may include obtaining two or more sets of images. The two or more sets of images may include a first image captured by a first image capture device and a second image captured by a second image capture device. The method may also include determining, for a set of images, two or more pairs of points. Each of the two or more pairs of points may include a first point in the first image and a second point in the second image, and the first point and the second point may correspond to a same object. The method may also include determining a first rotation matrix based on the pairs of points in the two or more sets of images. The first rotation matrix may be associated with a relationship between positions of the first image capture device and the second image capture device.

Methods and systems for camera calibration

The present disclosure relates to systems and methods for determining automatically a target field angle of an image capturing device. The method may include obtaining, by the image capturing device, at least two images for determining a target field angle of the image capturing device. The method may also include obtaining a field angle range of the image capturing device. Further, the method may include determining the target field angle by matching the at least two images based on the field angle range.

Systems and methods for determining a target field angle of an image capturing device

In accordance with various aspects of the present disclosure, methods and systems for fire detection are disclosed. In some embodiments, a method for fire detection includes: acquiring data related to a monitored area, wherein the data comprises image data related to the monitored area; determining, based on the acquired data, whether a first mode or a second mode is to be executed for fire detection, wherein the first mode comprises a first smoke detection, and the second mode comprises a first flame detection; and executing, by a hardware processor, at least one of the first mode or the second mode based on a result of the determination.

Methods and systems for fire detection

A system for video surveillance includes an image sensor configured capture an image including a reference zone and a memory device that stores instructions. The system also includes one or more processors that are configured to execute the instructions to determine 3D coordinates of a target comprised in the image and determine 3D coordinates of the reference zone. The one or more processors are further configured to identify an event according to the 3D coordinates of the target and the 3D coordinates of the reference zone.

Methods and systems for video surveillance

The present disclosure provides a system and method for generating a video synopsis. The method may include obtaining a video captured by a movable camera at a plurality of positions, the video including a sequence of video frames; determining, for each of at least part of the sequence of video frames, a position label of the video frame that indicates one of the plurality of positions of the movable camera; classifying the at least part of the sequence of video frames into a plurality of groups based on their position labels; determining one or more objects of interest in at least one of the plurality of groups; generating, for the at least one of the plurality of groups, a video synopsis based on the one or more objects of interest.

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Hangzhou, China

Huadong Pan