Techniques for machine learning based image attribute determination are disclosed. In some embodiments, one or more unknown attributes of a received image comprising a prescribed environment are determined using a machine learning based framework. The machine learning based framework is at least in part trained on image data sets comprising a model environment that substantially simulates the prescribed environment.

The present disclosure relates to systems and methods for image retrieval. The method may include obtaining an image retrieval request from a user device. The method may include identifying at least one target identification matching the image retrieval request from a plurality of candidate identifications in a database. Each of the plurality of candidate identifications may correspond to at least one candidate image and at least indicate position information associated with the at least one candidate image. The method may further include obtaining, based on the at least one target identification, at least one target image corresponding to the image retrieval request.

An information processing device includes a first obtaining unit that obtains, from an external information processing device, image information added to a captured image published for external access by the external information processing device under a preset obtainment condition, a first storage that stores the image information obtained by the obtaining unit, and a first controller that categorizes the image information stored in the first storage under a preset attribute condition. The image information includes at least positional information and time information each added to the captured image. The first controller categorizes the image information at least based on the positional information and the time information.

Embodiments of the present disclosure disclose a method and an apparatus for operating a control system, a storage medium, and an electronic apparatus. The method includes: obtaining, by using a target recording device in a control system, first image information of a target object moving in a real scene; obtaining a first distance corresponding to the first image information, the first distance being a distance between the target recording device and the target object; and adjusting a target parameter of the control system according to the first distance, the target parameter being used for outputting media information to a virtual reality (VR) device, the VR device being connected to the control system, the media information being corresponding to movement information of the target object moving in the real scene, and the movement information comprising the first distance.

An image processing method and apparatus is provided for obtaining an image captured by an image capturing apparatus; determining characteristic data of the captured image based on inputting the obtained image into an image analysis model trained with images including a predetermined type of characteristic data; and identifying, based on the determination performed by the image analysis model, metadata including a numeric value regarding the predetermined type of the captured image.

A method for retrieving footprint images is provided, comprising: pre-training models; cleaning footprint data and conducting expansion pre-processing by using the pre-trained models, dividing the footprint data into multiple data sets; adjusting full connection layers and classification layers of the models; training the models again by using the data sets through the parameters of the pre-trained models; saving the models trained twice, removing the classification layer, executing a feature extraction for images in an image library and a retrieval library to form a feature index library; connecting the features extracted by three models to form fused features, establishing a fused feature vector index library; extracting the features of the images in the image library to be retrieved in advance, and establishing a feature vector library; calculating distances in the retrieval library and the image library when a single footprint image is inputted, thereby outputting the image with the highest similarity.

A method for retrieving footprint images is provided, comprising: pre-training models; cleaning footprint data and conducting expansion pre-processing by using the pre-trained models, dividing the footprint data into multiple data sets; adjusting full connection layers and classification layers of the models; training the models again by using the data sets through the parameters of the pre-trained models; saving the models trained twice, removing the classification layer, executing a feature extraction for images in an image library and a retrieval library to form a feature index library; connecting the features extracted by three models to form fused features, establishing a fused feature vector index library; extracting the features of the images in the image library to be retrieved in advance, and establishing a feature vector library; calculating distances in the retrieval library and the image library when a single footprint image is inputted, thereby outputting the image with the highest similarity.

The present invention provides an information processing apparatus and a method of controlling the same. The information processing apparatus has a console unit that accepts an instruction by a user via a button displayed on a screen. The information processing apparatus registers a setting for executing processing corresponding to the button, prompts a user to input identification information to be added to image data generated by a function corresponding to the button, and when the button is instructed via the console unit, the information processing apparatus outputs the image data to which the identification information has been added to a destination corresponding to the setting which is registered in association with the button.

Provided is an electronic device including a display, a memory, and a processor operatively coupled with the display and the memory, wherein the processor is configured to obtain an image, output to a display a screen on which at least one Augmented Reality (AR) object is added to the obtained image, create a file including a capture image of the screen and information related to the at least one AR object in response to reception of a capture input for the screen, and store the file in the memory. In addition, various embodiments conceived through this document are possible.

Images are intelligently selected to create image narratives. Instead of a user having to manually search and locate images to view, the images to associate with a particular image narrative are programmatically determined. Many different types of image narratives may be created. For example, one image narrative may show images that include both a first user and a second user over some period of time. Another image narrative may show images that relate to an activity that a first user enjoys or an event that included the user (e.g., a graduation). The tags and metadata associated with the images of the user are analyzed to determine the tags that are important to the user. For example, the importance might be determined based on the frequency of the tags within the images. After creation, the user may select one of the image narratives to view the associated images.