下面是一段pami A.E. 给作者的回复，深有感触,再好的理论的再漂亮的模型，只有通过实验检验以后才有意义

To be accepted, a paper must present a clear, self-contained,scientifically convincing case for both the validity of its results and their usefulness. It therefore has to “work” at several levels. In particular, in applied fields like computer vision and especially for incremental improvements to established techniques such as those given here, theoretical results or algorithms seldom suffice: to demonstrate that the contribution will have an impact on actual practice, comparative experiments showing a clear practical advance over existing methods and establishing the limits of validity of the new approach are typically needed. Testing is essential because nice theoretical properties are not always a good guide to practical performance. It is not enough to provide a mere record of work done: you need to convince busy, skeptical practitioners who may already have working implementations to invest valuable time in understanding and perhaps reimplementing your method. Papers are published primarily to save other people effort so the onus of establishing the qualities of your method is on you, not on your readers.

From: Editorial-State of the Transactions(PAMI)  by David J. Kriegman, David Fleet