Mapping is an activity of making a useful description of an environment. Not only geometric information such as free space but also object placements are important if the map is used for human-robot communication. We call such a map making environment information summarization because how to summarize may change depending on the goal of the mapping and the context. Environment information summarization usually includes searching for specified objects in the environment. It is, therefore, crucial to make a good observation plan for efficient summarization. We develop an observation planning method which uses object appearance models for appropriately handling a trade-off between visual data quality and vision cost. Experimental results using a vision-based humanoid robot show the effectiveness of the proposed planning method.