Abstract: A method for detecting abnormal scene may include obtaining data relating to a video scene, identify at least two motion objects in the video scene based on the data and determining a first motion feature relating to the at least two motion objects based on the data. The method may also include determining a second motion feature relating to at least one portion of each of the at least two motion objects based on the data. The method may further include determining whether the at least two motion objects are involved in a fight based on the first motion feature and the second motion feature.

Abstract: A system for motion detection may include at least one storage medium that includes a set of instructions, and at least one processor in communication with the at least one storage medium. When executing the set of instructions, the at least one processor may be configured to cause the system to obtain data related to a video scene of a space from at least one video camera; detect an object in the video scene; classify the object as a human object or a non-human object; when the object is classified as a human object, track movements of the human object; and determine a posture of the human object in the video scene based on the movements of the human object.

Abstract: A method for traffic surveillance may include acquiring, from a plurality of first video sensors, a first set of images of an area, and generating a map-based surveillance interface of the area based on the first set of image data. The method may also include presenting, on a display, the map-based surveillance interface; wherein each of the plurality of first video sensors is implemented on an illuminating devices in the area, and the first set of image data denotes a plurality of views of the area captured by the plurality of first video sensors, respectively.

Abstract: A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network may include: obtaining a head image of a user with one or more dimension indicators, determining an eye region in the head image of the user and determining a pupillary distance of the user based on the one or more dimension indicators and the determined eye region. A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network may include: receiving a request at a user terminal, recording a video of a user wearing a wearable device with the user terminal, determining a pupillary distance of the user based on the video and synchronously displaying the pupillary distance on the video of the user during recording. The wearable device may include one or more dimension indicators.

Abstract: A system and method for determining a traffic sign violation are provided. The method may include obtaining a traffic rule corresponding to the traffic sign. The method may further include acquiring, by at least one camera, video data associated with a scene around a traffic sign. The video data may include a series of frames. The method may further include identifying the vehicle in the series of frames and determining whether the vehicle violates the traffic rule based on the series of frames. In response to the determination that the vehicle violates the traffic rule, the method may further include obtaining information of the vehicle and transmitting the information of the vehicle to a server.

Abstract: A method may include obtaining real-time image data relating to at least one scene acquired by a camera and identifying a plurality of real-time first features relating to a plurality of subjects from the real-time image data. The method may include determining one or more first estimated values corresponding to the plurality of real-time first features, the first estimated values being represented by a first coordinate system. The method may further include obtaining one or more first reference values corresponding to the plurality of real-time first features, the first reference values being represented by a second coordinate system, each of the first estimated values corresponding to one of the first reference values. The method may further include determining one or more real-time target parameters of the camera based on the first estimated values and the first reference values.

Abstract: A method for smart door operation implemented on a computer may include obtaining image data of one or more subjects. The image data may be acquired by one or more cameras in communication with the computer. The method may also include determining, based on the image data, one or more gait features of at least one of the one or more subjects and determining, at least in part based on the one or more gait features, identity information of the at least one of the one or more subjects. The method may further include sending an unlocking signal to a lock based on the unlocking signal so that the lock is unlocked.

Abstract: The system for lighting control may include a non-transitory storage medium storing executable instructions for lighting control, a communication component operatively connected to the non-transitory storage medium, at least one imaging device configured to capture images related to an area, and one or more illuminating device configured to light the area. The system may also include at least one processor in communication with the non-transitory storage medium. When executing the set of instructions, the at least one processor may cause the system to obtain image data relating to an area captured by the at least imaging device and determine at least one parameter relating to at least one of the one or more illuminating devices. The system may further include a control component configured to operate the at least one of the one or more illuminating devices to light the area based on the determined at least one parameter.

Abstract: A method may include obtaining a video collected by a visual sensor, the video including a plurality of frames and detecting one or more objects from the video in at least a portion of the plurality of frames. The method may also include determining a first detection result associated with the one or more objects with a trained self-learning model. The method may further include selecting a target moving object of interest from the one or more objects at least in part based on the first detection result. The trained self-learning model may be provided based on a plurality of training samples collected by the visual sensor.

Abstract: The present disclosure relates to systems and methods for retrieving image data. The systems may obtain a search request from a user device, the search request including at least one keyword. The systems may identify, in an image database, one or more target image archives associated with one or more target tags, respectively. The systems may retrieve, from the image database, the one or more target image archives, each of the one or more target image archives including a plurality of target images. The systems may transmit the one or more target image archives to the user device to be displayed via a user interface of the user device.

Abstract: A system and method for determining a traffic sign violation are provided. The method may include obtaining a traffic rule corresponding to the traffic sign. The method may further include acquiring, by at least one camera, video data associated with a scene around a traffic sign. The video data may include a series of frames. The method may further include identifying the vehicle in the series of frames and determining whether the vehicle violates the traffic rule based on the series of frames. In response to the determination that the vehicle violates the traffic rule, the method may further include obtaining information of the vehicle and transmitting the information of the vehicle to a server.

Abstract: A method for smart door operation implemented on a computer may include obtaining image data of one or more subjects. The image data may be acquired by one or more cameras in communication with the computer. The method may also include determining, based on the image data, one or more gait features of at least one of the one or more subjects and determining, at least in part based on the one or more gait features, identity information of the at least one of the one or more subjects. The method may further include sending an unlocking signal to a lock based on the unlocking signal so that the lock is unlocked.

Abstract: A method for traffic surveillance may include acquiring, from a plurality of first video sensors, a first set of images of an area, and generating a map-based surveillance interface of the area based on the first set of image data. The method may also include presenting, on a display, the map-based surveillance interface; wherein each of the plurality of first video sensors is implemented on an illuminating devices in the area, and the first set of image data denotes a plurality of views of the area captured by the plurality of first video sensors, respectively.

Abstract: A method for detecting abnormal scene may include obtaining data relating to a video scene, identify at least two motion objects in the video scene based on the data and determining a first motion feature relating to the at least two motion objects based on the data. The method may also include determining a second motion feature relating to at least one portion of each of the at least two motion objects based on the data. The method may further include determining whether the at least two motion objects are involved in a fight based on the first motion feature and the second motion feature.

Abstract: The system for lighting control may include a non-transitory storage medium storing executable instructions for lighting control, a communication component operatively connected to the non-transitory storage medium, at least one imaging device configured to capture images related to an area, and one or more illuminating device configured to light the area. The system may also include at least one processor in communication with the non-transitory storage medium. When executing the set of instructions, the at least one processor may cause the system to obtain image data relating to an area captured by the at least imaging device and determine at least one parameter relating to at least one of the one or more illuminating devices. The system may further include a control component configured to operate the at least one of the one or more illuminating devices to light the area based on the determined at least one parameter.

Abstract: A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network may include: obtaining a head image of a user with one or more dimension indicators, determining an eye region in the head image of the user and determining a pupillary distance of the user based on the one or more dimension indicators and the determined eye region. A method implemented on a computing device having at least one processor, storage, and a communication platform connected to a network may include: receiving a request at a user terminal, recording a video of a user wearing a wearable device with the user terminal, determining a pupillary distance of the user based on the video and synchronously displaying the pupillary distance on the video of the user during recording. The wearable device may include one or more dimension indicators.