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In this paper, we consider the problem where a point robot in a 2D or 3D environment equipped with an omnidirectional range sensor of finite range D is asked to cover a set of surface patches, while minimizing the sum of view cost, proportional to the number of viewpoints planned, and the travel cost, proportional to the length of path traveled. We call it the Metric View Planning Problem with Traveling Cost and Visibility Range or Metric TVPP in short. We present a complexity result for the problem, i.e., we show that the Metric TVPP cannot be approximated within O(log m) ratio by any polynomial algorithm, where m is the number of surface patches to cover. We then analyze a variant of an existing decoupled two-level algorithm of first solving the view planning problem to get an approximate solution, and then solving, again using an approximation algorithm, the Metric traveling salesman problem to connect the planned viewpoints. We then present performance bounds for this two-level decoupled algorithm, i.e., we show that it has an approximation ratio of O(log m). Thus, it asymptotically achieves the best approximation ratio one can hope for.