Embedded computer vision is a hot field of research that requires trade-offs in order to
balance execution time, power consumption and accuracy. In that field, dense optical flow …

This article presents and compares optimized implementations of two optical flow algorithms
on several target boards comprising multi-core SIMD processors and GPUs. The two …

High-speed corner detection is an essential step in many real-time computer vision
applications, eg, object recognition, motion analysis, and stereo matching. Hardware …

The emergence of low-power embedded Graphical Processing Units (GPUs) with high
computation capabilities has enabled the integration of image processing chains in a wide …

This work proposes a highly tunable motion estimation architecture. We implement the Horn
and Schunck algorithm with the hierarchical extension for larger motion estimations in …

The goal of this article is to compare some optimised implementations on current high
performance platforms in order to highlight architectural trends in the field of embedded …

Low-complexity corner detection is essential for many real-time computer vision applications
that need to be executed on low-cost/low-power embedded platforms such as robots. The …

Corner detection plays an essential role in many computer vision applications, eg, object
recognition, motion analysis and stereo matching. Several hardware implementations of …

Stream-based image processing architectures are extremely attractive as they can achieve
high throughput and do not require external memories for storing input video frames …

Pour beaucoup d'applications, la présence de bruit dans les vidéos peut être un problème
majeur. Des algorithmes de débruitage existent, la plupart sont qualitativement très efficaces …