Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Computer Vision Accelerators for Mobile Systems based on OpenCL GPGPU
  Co-Processing   In this paper, we present an OpenCL-based heterogeneous implementation of a
computer vision algorithm -- image inpainting-based object removal algorithm --
on mobile devices. To take advantage of the computation power of the mobile
processor, the algorithm workflow is partitioned between the CPU and the GPU
based on the profiling results on mobile devices, so that the
computationally-intensive kernels are accelerated by the mobile GPGPU
(general-purpose computing using graphics processing units). By exploring the
implementation trade-offs and utilizing the proposed optimization strategies at
different levels including algorithm optimization, parallelism optimization,
and memory access optimization, we significantly speed up the algorithm with
the CPU-GPU heterogeneous implementation, while preserving the quality of the
output images. Experimental results show that heterogeneous computing based on
GPGPU co-processing can significantly speed up the computer vision algorithms
and makes them practical on real-world mobile devices.

22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
2
The categories of this paper are: math