USEQ: Ultra-fast superpixel extraction via quantization

Chun-Rong Huang, Wei-An Wang, Szu-Yu Lin, Yen-Yu Lin

Abstract: We propose a novel superpixel extraction method named USEQ to generate regular and compact superpixels. To reduce the computational burden of iterative optimization procedures used in most recent approaches, the spatial and color quantizations are performed in advance to represent pixels and superpixels. Maximum a posteriori estimation in both pixel and region levels is then adopted to aggregate pixels into spatially and visually coherent superpixels. The resultant superpixels are extremely efficient to generate and can more precisely adhere to object boundaries. Compared to the state-of-the-art approaches to superpixel extraction, USEQ can achieve better or competitive performance in terms of boundary recall, undersegmentation error and achievable segmentation accuracy, and is significantly faster than these approaches.