Abstract: This disclosure provides systems, methods, and devices for image capture using an autofocus (AF) algorithm. In a first aspect, a method for autofocus includes receiving first image data of a first scene from a first image sensor of a first camera, the first image data comprising phase shift information; determining a first focal distance for the first scene based on a machine learning algorithm by inputting the phase shift information to the machine learning algorithm; and controlling a focal position of the first camera based on the first focal distance. Other aspects and features are also claimed and described.

Abstract: This disclosure provides systems, methods, and devices for image capture using an autofocus (AF) algorithm. In a first aspect, a method for autofocus includes receiving first image data of a first scene from a first image sensor of a first camera, the first image data comprising phase shift information; determining a first focal distance for the first scene based on a machine learning algorithm by inputting the phase shift information to the machine learning algorithm; and controlling a focal position of the first camera based on the first focal distance. Other aspects and features are also claimed and described.

Abstract: Disclosed are systems, apparatuses, processes, and computer-readable media to capture images with subjects at different depths of fields. A method of processing image data includes determining, based on a depth map of a previously captured image, a first distance to a first object and a second distance to a second object; identifying a focal point of a camera lens at least in part using the first distance and the second distance; capturing an image using the focal point as a basis for the capture, the image including a first region corresponding to the first object and a second region corresponding to the second object; and generating a second image from the image at least in part by enhancing at least one of the first region or the second region using a point spread function (PSF).

Abstract: Systems and techniques described herein relate to techniques for improving image detection. In some examples, aspects relate to systems and techniques for improving image detection by performing tracking of objects within captured image frames. A process can include obtaining, from an image capture device, a first image frame including an object. The process can further include determining, using an object detector, an object validation score associated with detection of the object in the first image frame, and determining the object validation score is less than a validation threshold. Based on the object validation score being less than the validation threshold, the process can include tracking the object for one or more image frames received subsequent to the first image frame.

Abstract: An image processing device receives image data from an image frame captured by an image sensor of an image capture device. The image processing device moves a lens of the image capture device while still receiving the image data from the image frame, for instance as part of an autofocus operation. The image processing device determines multiple positions of the lens from the beginning of the movement to the end of the movement based on a lens position sensor, based on differences between the image frame and other consecutive image frames, or based on interpolation. The image processing device performs field of view compensation on the image data by cropping one or more rows of the image data based on the positions of the lens.