Apollo Intelligent Driving Technology (beijing) Co., Ltd.

Beijing Bolian Times Commercial Plaza Co., Ltd.

Guo Li

Ming Wang

Xun Sun

Han Gao

The present invention relates to wearable smart devices and neural engineering, disclosing a cognitive accessory that combines a brain-computer interface (BCI) with smart glasses, which includes an in-ear electrode module equipped with a plurality of EEG electrodes, a smart glasses frame with temples on both sides, a nose pad at the bottom of the frame, and two lenses installed on the frame. The smart glasses frame integrates a non-invasive brain signal acquisition module, an environmental perception module, an embedded processor, and an AR display module. The brain signal acquisition module uses flexible electrodes distributed inside the nose pad and the temples. By integrating flexible EEG electrodes and miniature fNIRS probes within the smart glasses frame, users can achieve efficient, non-invasive monitoring of brain electrical activity and cerebral blood oxygenation without wearing traditional complex headgear. This design makes the device more lightweight, comfortable, and convenient for long-term wear.

Cognitive accessory combining brain-computer interface and smart glasses

Embodiments of the present provide a cross-camera obstacle tracking method, system and medium. The method includes: obtaining obstacle tracking results of images captured by at least two cameras, wherein each obstacle tracking result comprises results after identifying and tracking at least one obstacle in the image captured by each camera, and each obstacle is labeled with a local identifier for each camera; in response to a triggering condition of a main camera in the cameras to fusion of cross-camera obstacles being satisfied, establishing a mapping relation between local identifiers of the obstacles in the cameras and global identifiers according to the obstacle tracking result of each of the cameras; determining similarities of obstacles according to the obstacle tracking result of each of the cameras, and performing fusion of the global identifiers on the same obstacle according to the similarities; and obtaining final obstacle tracking results labeled with the global identifiers.

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Beijing, China

Guo Li