Abstract
We present a new framework for generic and adaptive memoryless surface simplification. We show that many existing techniques of simplification based on the edge collapse / vertex split operations differ only in terms of memory-resident data used to improve running performance. By removing the need for this memory we are able to implement multiple simplification techniques on the same platform. Our generic platform can be used as a tool for the generation and evaluation of custom error metrics. We present two new error metrics designed using our generic framework. We present a novel batched ordering technique based on the generic simplification framework, which allows for adaptive simplification and automatic level-of-detail generation.
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