A processor implemented method comprising: acquiring successive frames, in real time, from multiple views captured by a monocular camera located in a simultaneous localization and mapping (SLAM) environment and characterized by multiple unknown poses ; detecting edges in each of the successive frames ; thinning the edges of each of the successive frames to obtain thinned edges having a single pixel width ; applying an edge filtering process on the thinned edges to eliminate noise therein ; estimating point feature correspondences of edge points constituting the thinned edges by tracking the edge points using an optical flow ; identifying a first frame as a keyframe and further identifying a plurality of keyframes, from the acquired successive frames, based on the estimated point feature correspondences and satisfying a first set of constraints ; performing a two-view initialization using a selected pair of keyframes from the plurality of keyframes satisfying a second set of constraints to obtain a validated 3D structure ; estimating a trajectory of estimated poses from the multiple unknown poses of the monocular camera by obtaining incremental poses based on the validated 3D structure constituting 3D structure points ; and rectifying drifts in the estimated trajectory captured in the multiple views using loop closure , wherein the loop closure comprises of: performing loop detection for finding loops in the estimated trajectory; performing loop merging for correcting drifts in the estimation of the current keyframe and a subsequent keyframe. acquiring successive frames, in real time, from multiple views captured by a monocular camera located in a simultaneous localization and mapping (SLAM) environment and characterized by multiple unknown poses ; detecting edges in each of the successive frames ; thinning the edges of each of the successive frames to obtain thinned edges having a single pixel width ; applying an edge filtering process on the thinned edges to eliminate noise therein ; estimating point feature correspondences of edge points constituting the thinned edges by tracking the edge points using an optical flow ; identifying a first frame as a keyframe and further identifying a plurality of keyframes, from the acquired successive frames, based on the estimated point feature correspondences and satisfying a first set of constraints ; performing a two-view initialization using a selected pair of keyframes from the plurality of keyframes satisfying a second set of constraints to obtain a validated 3D structure ; estimating a trajectory of estimated poses from the multiple unknown poses of the monocular camera by obtaining incremental poses based on the validated 3D structure constituting 3D structure points ; and rectifying drifts in the estimated trajectory captured in the multiple views using loop closure , wherein the loop closure comprises of: performing loop detection for finding loops in the estimated trajectory; performing loop merging for correcting drifts in the estimation of the current keyframe and a subsequent keyframe. performing loop detection for finding loops in the estimated trajectory; performing loop merging for correcting drifts in the estimation of the current keyframe and a subsequent keyframe. <EOS>