A processor-implemented method for determining camera pose information, the method being applied to a mobile terminal having a camera, wherein the method comprises: obtaining a first image, a second image, and a template image, the first image being a previous frame of image of the second image, the first image and the second image being images collected by the camera, and the template image being a reference image used for matching; performing feature point detection on a first feature point in the template image and a second feature point in the second image, to obtain a first homography, wherein the template image includes a plurality of image layers, and the template image in an original size is downsampled to generate a pyramid image, and wherein feature points for each layer of the pyramid image are extracted, and for feature points not extracted from the pyramid image in an original scale, after the pyramid image is scaled up to the original scale according to the scaling proportion, two-dimensional coordinates of each feature point on the pyramid image in the original scale are recorded, wherein the feature points on the pyramid image and the two-dimensional coordinates are referred to as the first feature points; determining a first target homography according to a first optical flow feature point in the first image and a second optical flow feature point in the second image, and determining a second homography according to the first target homography and a second target homography, the second target homography being a homography from the template image to the first image; and performing complementary filtering processing on the first homography and the second homography, to obtain camera pose information of the camera, wherein the template image corresponds to a plurality of grids arranged in arrays; and the operation of performing feature point detection on a first feature point in the template image and a second feature point in the second image, to obtain a first homography comprises: matching the first feature point in the template image with the second feature point in the second image, and determining a set of feature point pairs in each target grid of the plurality of grids, the feature point pair comprising: a first feature point located in the target grid, and a feature point that is in the second feature point and that has the largest matching degree with the first feature point; and calculating the first homography between the template image and the second image according to the feature point pairs in the target grid. obtaining a first image, a second image, and a template image, the first image being a previous frame of image of the second image, the first image and the second image being images collected by the camera, and the template image being a reference image used for matching; performing feature point detection on a first feature point in the template image and a second feature point in the second image, to obtain a first homography, wherein the template image includes a plurality of image layers, and the template image in an original size is downsampled to generate a pyramid image, and wherein feature points for each layer of the pyramid image are extracted, and for feature points not extracted from the pyramid image in an original scale, after the pyramid image is scaled up to the original scale according to the scaling proportion, two-dimensional coordinates of each feature point on the pyramid image in the original scale are recorded, wherein the feature points on the pyramid image and the two-dimensional coordinates are referred to as the first feature points; determining a first target homography according to a first optical flow feature point in the first image and a second optical flow feature point in the second image, and determining a second homography according to the first target homography and a second target homography, the second target homography being a homography from the template image to the first image; and performing complementary filtering processing on the first homography and the second homography, to obtain camera pose information of the camera, wherein the template image corresponds to a plurality of grids arranged in arrays; and the operation of performing feature point detection on a first feature point in the template image and a second feature point in the second image, to obtain a first homography comprises: matching the first feature point in the template image with the second feature point in the second image, and determining a set of feature point pairs in each target grid of the plurality of grids, the feature point pair comprising: a first feature point located in the target grid, and a feature point that is in the second feature point and that has the largest matching degree with the first feature point; and calculating the first homography between the template image and the second image according to the feature point pairs in the target grid. matching the first feature point in the template image with the second feature point in the second image, and determining a set of feature point pairs in each target grid of the plurality of grids, the feature point pair comprising: a first feature point located in the target grid, and a feature point that is in the second feature point and that has the largest matching degree with the first feature point; and calculating the first homography between the template image and the second image according to the feature point pairs in the target grid.