Compact Watershed and Preemptive SLIC: On Improving Trade-offs of Superpixel Segmentation Algorithms

A major insight from our previous work on extensive comparison of super pixel segmentation algorithms is the existence of several trade-offs for such algorithms. The most intuitive is the trade-off between segmentation quality and runtime. However, there exist many more between these two and a multitude of other performance measures. In this work, we present two new super pixel segmentation algorithms, based on existing algorithms, that provide better balanced trade-offs. Better balanced means, that we increase one performance measure by a large amount at the cost of slightly decreasing another. The proposed new algorithms are expected to be more appropriate for many real time computer vision tasks. The first proposed algorithm, Preemptive SLIC, is a faster version of SLIC, running at frame-rate (30 Hz for image size 481x321) on a standard desktop CPU. The speed-up comes at the cost of slightly worse segmentation quality. The second proposed algorithm is Compact Watershed. It is based on Seeded Watershed segmentation, but creates uniformly shaped super pixels similar to SLIC in about 10 ms per image. We extensively evaluate the influence of the proposed algorithmic changes on the trade-offs between various performance measures.