High Speed Skin Color Detection and Localization on a GPU

I grew interested in trying to understand the American approach and the reasons behind the current American influence in medicine, and left The Norwegian University of Science

Each community in the first group is handled by one warp, while communities in the second group are assigned to one thread block, both using shared memory to store the hash

To compare the speed of our method against a possible GPU implementa- tion of visibility rasterization, we rendered 32 × 32 visibility masks as seen from each of the 2978 vertices

We have implemented the FEM method in the GPU and compare its performance with the implementation, also in the GPU, of the mass-spring model and with the first GPU implementation of

In this paper, we present a simple yet novel method for high speed skin color detection and localization on images and video using the Graphics Processing Unit (GPU) and common

With a GPU, our method achieved up to 36.5 times higher performance for the ray-casting process, and 18.1 times higher performance for the entire volume rendering, compared with

We have applied our method to a deep learning model for semantic segmentation, U-Net, in a remote sensing application of building detection.. This application is of high interest

Moreover, the search for lines close to a given pixel can be done efficiently by using this GPU-based vector map data structure, and the pixel can be colored based on the distance