A method of parallax tolerant video stitching, the method comprising: determining a plurality of video sequences to be stitched together; performing a spatial-temporal localized warping computation process on the video sequences to determine a plurality of target warping maps; warping a plurality of frames among the video sequences into a plurality of target virtual frames using the target warping maps; performing a spatial-temporal content-based seam finding process on the target virtual frames to determine a plurality of target seam maps; and stitching the video sequences together using the target seam maps; wherein the spatial-temporal localized warping computation process comprises: determining a plurality of spatial global homographies and a plurality of temporal global homographies using a plurality of visual keypoints associated with the video sequences; performing a pre-warping process, using the spatial global homographies and the temporal global homographies, to obtain a plurality of pre-warped temporal matching pairs and a plurality of pre-warped spatial matching pairs; determining a plurality of target vertices using the pre-warped temporal matching pairs and the pre-warped spatial matching pairs; and determining the plurality of target warping maps using the target vertices; and wherein the spatial-temporal content-based seam finding process comprises: performing a spatial-temporal objectness computation using the target virtual frames to determine a plurality of spatial-temporal objectness values; determining a graph comprising nodes, spatial edges and temporal edges connecting the nodes, where each node represents an overlapping pixel between target virtual frames, and said edges are defined taking into account the objectness of the pixels; labeling each of the nodes as either source or sink by finding an optimal path to cut the graph; and determining the target seam maps using the labeled nodes, wherein the seam maps are used to stitch the video sequences together. determining a plurality of video sequences to be stitched together; performing a spatial-temporal localized warping computation process on the video sequences to determine a plurality of target warping maps; warping a plurality of frames among the video sequences into a plurality of target virtual frames using the target warping maps; performing a spatial-temporal content-based seam finding process on the target virtual frames to determine a plurality of target seam maps; and stitching the video sequences together using the target seam maps; wherein the spatial-temporal localized warping computation process comprises: determining a plurality of spatial global homographies and a plurality of temporal global homographies using a plurality of visual keypoints associated with the video sequences; performing a pre-warping process, using the spatial global homographies and the temporal global homographies, to obtain a plurality of pre-warped temporal matching pairs and a plurality of pre-warped spatial matching pairs; determining a plurality of target vertices using the pre-warped temporal matching pairs and the pre-warped spatial matching pairs; and determining the plurality of target warping maps using the target vertices; and wherein the spatial-temporal content-based seam finding process comprises: performing a spatial-temporal objectness computation using the target virtual frames to determine a plurality of spatial-temporal objectness values; determining a graph comprising nodes, spatial edges and temporal edges connecting the nodes, where each node represents an overlapping pixel between target virtual frames, and said edges are defined taking into account the objectness of the pixels; labeling each of the nodes as either source or sink by finding an optimal path to cut the graph; and determining the target seam maps using the labeled nodes, determining a plurality of spatial global homographies and a plurality of temporal global homographies using a plurality of visual keypoints associated with the video sequences; performing a pre-warping process, using the spatial global homographies and the temporal global homographies, to obtain a plurality of pre-warped temporal matching pairs and a plurality of pre-warped spatial matching pairs; determining a plurality of target vertices using the pre-warped temporal matching pairs and the pre-warped spatial matching pairs; and determining the plurality of target warping maps using the target vertices; and wherein the spatial-temporal content-based seam finding process comprises: performing a spatial-temporal objectness computation using the target virtual frames to determine a plurality of spatial-temporal objectness values; determining a graph comprising nodes, spatial edges and temporal edges connecting the nodes, where each node represents an overlapping pixel between target virtual frames, and said edges are defined taking into account the objectness of the pixels; labeling each of the nodes as either source or sink by finding an optimal path to cut the graph; and determining the target seam maps using the labeled nodes, performing a spatial-temporal objectness computation using the target virtual frames to determine a plurality of spatial-temporal objectness values; determining a graph comprising nodes, spatial edges and temporal edges connecting the nodes, where each node represents an overlapping pixel between target virtual frames, and said edges are defined taking into account the objectness of the pixels; labeling each of the nodes as either source or sink by finding an optimal path to cut the graph; and determining the target seam maps using the labeled nodes,