This paper is a general overview of the SKIPPER KIPPER project, run at Blaise Pascal University between 1996 and 2002. The main goal of the SKIPPER KIPPER project was to demonstrate the applicability of skeleton-based parallel programming techniques to the fast prototyping of reactive vision applications. This project has produced several versions of a full-fledged integrated parallel programming environment (PPE). These PPEs have been used to implement realistic vision applications, such as road following or vehicle tracking for assisted driving, on embedded parallel platforms embarked on semi-autonomous vehicles. All versions of SKIPPER KI PPER share a common front-end and repertoire of skeletons--presented in previous papers--but differ in the techniques used for implementing skeletons. This paper focuses on these implementation issues, by making a comparative survey, according to a set of four criteria (efficiency, expressivity, portability, predictability), of these implementation techniques. It also gives an account of the lessons we have learned, both when dealing with these implementation issues and when using the resulting tools for prototyping vision applications.