Abstract
A system for detecting an important event/occasion and automatic capturing of image/video is disclosed. A photographer AI (artificial intelligence) app is installed on a mobile device of each user. The users (who are going out on an event) are connected in a peer-to-peer network on the photographer AI app. Each user shares her/his live location on a platform of the photographer AI app. The photographer AI app determines whether a subset of the users is in proximity (i.e. in range and in a frame) for a good picture. The subset of users in the proximity is determined using their live locations and a location sensor of the mobile device. An HMD (Head Mounted Display) device wirelessly interfaces with the photographer AI app. A camera, embedded in the HMD device, captures a video of the surroundings. The video is fed as an input to a trained photographer AI (artificial intelligence) function if the subset of the users is in the proximity for a good picture. The trained photographer AI function detects an emotion associated with the subset of the users in the video. If a positive emotion such as laughter, cheerful screaming for the subset of the users is detected, the camera starts capturing image(s)/video(s). A person identification module of the photographer AI app identifies user(s) in the subset of the users. The captured image(s)/video(s) is/are sent to the platform of the photographer AI app and are encrypted using encryption key(s). The encryption key(s) is/are owned by the user(s) in the subset of the users.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, Anonymous, "Secure Crowd-sourced Photography", Technical Disclosure Commons, (October 16, 2019)
https://www.tdcommons.org/dpubs_series/2569