20. The computer-readable medium of claim 19 , wherein the method further comprises: creating a unit sphere, each hypothesis being located on a surface of the sphere; dividing the unit sphere into multiple bins of equal size; identifying the bin that contains the largest number of hypotheses; and setting the mode as the center of the identified bin or the center of a dominant cluster of hypotheses within the identified bin.
19. A non-transitory computer-readable medium having encoded thereon executable instructions that, when executed by at least one processor, cause the at least one processor to carry out a method for guidance and navigation of an autonomous vehicle, the autonomous vehicle comprising at least one camera, the method comprising: processing a plurality of images of an environment of the autonomous vehicle captured using the at least one camera of the autonomous vehicle over a period of time to track one or more objects within the environment, wherein processing the plurality of images to track the one or more objects in the environment comprises processing at least two images of the plurality of images to estimate a pose of a first object in the environment, wherein processing the at least two images to estimate the pose of the first object comprises: identifying matching feature points between sequential images; generating hypotheses for a pose component of the pose of the first object; identifying a mode of a probability mass function associated with the hypotheses; extracting low-noise hypotheses; and averaging the low-noise hypotheses to obtain an estimate for the pose component of the pose of the first object.