The invention discloses a real-time object tracking method based on video inter-frame low-rank associated information consistency. The method comprises the following steps: during the target object characteristic description period, giving position information in an initial video by a user at first and then performing characteristic description on a target object and a candidate region in a next frame by compressive sensing of local restrictions; during the inter-frame low-rank association analysis period, extracting key descriptions from a target object characteristic library to form a local characteristic library, and performing low-rank decomposition on the local characteristic library and the characteristic descriptions of the candidate region together to obtain a sparse matrix; calculating an inter-frame low-rank associated prior and cover mask; outputting a current target object position according to the sparse matrix and the inter-frame low-rank associated prior and cover mask; updating a target library, performing global low-rank analysis on a target characteristic library, and replacing the low-rank description with the best commonality with a current target object description. The method is capable of stably tracking a single object in the video for a long time in real time, and has the characteristics of high tracking speed, high tracking precision and the like.