1. A method of object detection, the method comprising; receiving a first image taken from a first perspective by a first camera of a head mounted display; receiving a second image taken from a second perspective, different from the first perspective, by a second camera of the head mounted display; offsetting each pixel in the first image relative to a corresponding pixel in the second image by a predetermined offset distance resulting in offset first and second images, wherein a particular pixel of the offset first image depicts a same object locus as a corresponding pixel in the offset second image only if the object locus is at a desired object-detection distance from the head mounted display; applying a machine-learning trained classifier to the offset first image to determine a first confidence of object detection for each pixel in the offset first image; applying the machine-learning trained classifier to the offset second image to determine a second confidence of object detection for each pixel in the offset second image; for each pixel in the offset first image, correlating the first confidence of object detection to the second confidence of object detection of a corresponding pixel in the offset second image; and based on the first confidence, the second confidence, and correlation between the first and second confidences, identifying one or more pixels in the offset first and second images as depicting a target object.