Demo Data from VLDB 2026 / reviewers in the wild / expert
Hideaki Murayama
dblp:39/9967
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2011
0000-0002-8049-2329ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 100% |
Topics — the 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Hardware accelerators and domain-specific architectures
optical flow computation |
0.1 | 1 | 2011 | Design of a miniature, multi-directional optical flow sensor for Micro Aerial Vehicles · ICRA 2011 |
Methods — techniques the papers use, named apart from their topics
FPGA implementation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Design of a miniature, multi-directional optical flow sensor for Micro Aerial VehiclesabstractAs Micro Aerial Vehicles (MAVs) become smaller, the correspondingly smaller payload capacity greatly limits the type and number of sensors which can be carried. Biologically inspired visual sensors based on optical flow show great promise due to the small size of the image sensors needed to capture visual data, but the high computational cost is a limiting factor. Current optical flow sensors are either small with very low resolution, or high resolution with large computing requirements, making them unsuitable for the primary sensor for MAVs. This paper presents an optical flow sensor specifically de signed for the needs of MAVs, combining very small size with adequate resolution and the capability of processing many image sensors in a single FPGA. Initial results indicate that per formance is sufficient for MAVs, and optical flow calculations can be performed in real-time with image sensors operating at 320×240 resolution at up to 120 FPS. FPGA resource usage estimates indicate that a 15×15 mm FPGA can calculate 2D optical flow for up to 11 image sensors simultaneously. Daniel Watman, Hideaki Murayama |
ICRA | 2 |