In order to solve template updating, basis construction and low efficiency problems in visual tracking tasks, a
novel algorithm based on the space-time constrained and sparse representation classification is proposed. The details of
space constraint, time constraint, both target and background basis construction methods, basis choosing, basis abandoning
mechanisms and temporal feature pool construction methods are given. The temporal looping updating method is used to
solve the template updating problem. The sparse representation classification method and normal hedge are combined for
calculating target locations. The proposed tracking algorithm outperforms better than other state-of-art tracking algorithms
in many difficult situations.