For the requirement of many practical applications in the area of industry and medicine

the research in three-dimensional objects recognition is very active. In general

the dominant paradigm in 3D objects recognition system proposes to achieve recognition and localization of 3D objects from images by a two-stage process: first derive an internal representation of a scene from the sensed input data and then match it against stored representations of objects in the database. This paper presents a comprehensive survey of the achievement of 3D objects recognition system in the recent decade. The three problems are discussed which are the type of sensors used

3D objects representation and match strategy. Furthermore

the paper classifies and summarizes the primary schemes. At last

we describe some problems requiring a thorough research on three-dimensional vision system

such as the limitation by the class of shapes that can be described in most of the representation schemes

the clustered background influence on the recognition

and the contradiction between global and local in the 3D objects representation and recognition.