A display request including designation related to a display state of a stereoscopic shape in a three-dimensional space is transmitted from a receiving apparatus 200 to a transmitting apparatus 100, and the transmitting apparatus 100 extracts point cloud data of a part corresponding to the display request from among the point cloud data stored in a point cloud data storage unit 10 in response to the display request and transmits the extracted point cloud data to the receiving apparatus 200. Accordingly, only the point cloud data of the part which is necessary for the display state of the stereoscopic shape which is actually displayed in the three-dimensional space by the receiving apparatus 200 is transmitted, and thus it is possible to transmit only the point cloud data necessary for display within a practically acceptable short time on a communication network 300 even though the entire data amount of the point cloud data stored in the point cloud data storage unit 10 is huge.

An image processing method, a non-transitory computer-readable storage medium, and an electronic apparatus are disclosed. The method includes: acquiring a first initial image by a first camera at a first frame rate during an exposure period, and acquiring at least two second initial images by a second camera at a second frame rate during the exposure period; and stitching the at least two second initial images into one second target image; wherein the second target image is a depth image. The first frame rate is less than the second frame rate, and each second initial image is an image comprising depth information.

A digital photographing apparatus is provided. The digital photographing apparatus includes a first optical system configured to acquire a wide-angle image including a subject, a second optical system configured to acquire a telephoto image with the subject zoomed, and a processor configured to determine whether to generate a synthesized image of the wide-angle image and the telephoto image based on one or more of an illuminance of the subject and a distance between the digital photographing apparatus and the subject.

Systems and methods in accordance with embodiments of the invention are configured to render images using light field image files containing an image synthesized from light field image data and metadata describing the image that includes a depth map. One embodiment of the invention includes a processor and memory containing a rendering application and a light field image file including an encoded image, a set of low resolution images, and metadata describing the encoded image, where the metadata comprises a depth map that specifies depths from the reference viewpoint for pixels in the encoded image. In addition, the rendering application configures the processor to: locate the encoded image within the light field image file; decode the encoded image; locate the metadata within the light field image file; and post process the decoded image by modifying the pixels based on the depths indicated within the depth map and the set of low resolution images to create a rendered image.

Systems and methods in accordance with embodiments of the invention are configured to render images using light field image files containing an image synthesized from light field image data and metadata describing the image that includes a depth map. One embodiment of the invention includes a processor and memory containing a rendering application and a light field image file including an encoded image, a set of low resolution images, and metadata describing the encoded image, where the metadata comprises a depth map that specifies depths from the reference viewpoint for pixels in the encoded image. In addition, the rendering application configures the processor to: locate the encoded image within the light field image file; decode the encoded image; locate the metadata within the light field image file; and post process the decoded image by modifying the pixels based on the depths indicated within the depth map and the set of low resolution images to create a rendered image.

A method of distance measuring includes obtaining a depth map and a stereo pair of images of a scene of interest, and enhancing a precision of the depth map based on disparity values of corresponding points between the images. The images have a higher resolution than the depth map. Enhancing the precision of the depth map includes optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; determining the disparity values based on the optimized energy function; and replacing low precision values of the depth map with corresponding high precision values based on the disparity values.

A method of distance measuring includes obtaining a depth map and a stereo pair of images of a scene of interest, and enhancing a precision of the depth map based on disparity values of corresponding points between the images. The images have a higher resolution than the depth map. Enhancing the precision of the depth map includes optimizing an energy function of the images over a predetermined range of disparity values to obtain an optimized energy function; determining the disparity values based on the optimized energy function; and replacing low precision values of the depth map with corresponding high precision values based on the disparity values.

A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.

A method for training a depth estimation model and methods for use thereof are described. Images are acquired and input into a depth model to extract a depth map for each of the plurality of images based on parameters of the depth model. The method includes inputting the images into a pose decoder to extract a pose for each image. The method includes generating a plurality of synthetic frames based on the depth map and the pose for each image. The method includes calculating a loss value with an input scale occlusion and motion aware loss function based on a comparison of the synthetic frames and the images. The method includes adjusting the plurality of parameters of the depth model based on the loss value. The trained model can receive an image of a scene and generate a depth map of the scene according to the image.

Aspects of the disclosure relate to an apparatus including multiple image sensors sharing one or more optical paths for imaging. An example method includes identifying whether a device including a first aperture, a first image sensor, a second image sensor, and an optical element is to be in a first device mode or a second device mode. The method also includes controlling the optical element based on the identified device mode. The optical element directs light from the first aperture to the first image sensor in a first optical element mode. Light from the first aperture is directed to the second image sensor when the optical element is in the second optical element mode.