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Tsutomu Ito

dblp:145/2202 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author

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.

Artificial intelligence
1 paper
3D vision · 87% Robot navigation and mapping · 13%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › range sensing
depth sensing
0.011990
Fast range scanner using an optic RAM · ICRA 1990
Computer vision › 3D vision › range sensing › depth sensing
range image
0.011990
Fast range scanner using an optic RAM · ICRA 1990
Robotics › Robot navigation and mapping
sensor design
0.011990
Fast range scanner using an optic RAM · ICRA 1990

Methods — techniques the papers use, named apart from their topics

triangulation · 0.0optic RAM · 0.0lookup table · 0.0
YearPublicationVenuePosition
1990 Fast range scanner using an optic RAM
abstract
A range scanner which calculates ranges by triangulation between the incident angles of laser stripes and the positions of their images on a camera sensor was developed for robotic applications. It uses a solid-state image sensor called Optic RAM instead of a CCD sensor. This sensor chip has three desirable characteristics for the position detection of laser stripes in images: it thresholds the image, detecting only the brighter stripes in binary form; it is an image memory; and pixel values can be addressed randomly in the image. Thus, the design does not require an A/D converter or a frame buffer and is consequently inexpensive. For improved performance, only the image region next to the previous stripe location is searched, and a 64-KB lookup table stored in RAM is indexed by incident laser angles and stripe addresses to output range data. A 128*256 range image is produced in about 20 s. This is reasonably fast considering that this process requires analyzing 256 images. The speed bottleneck is the low sensitivity of the optic RAM chip, which requires a long exposure time per frame (60 ms), corresponding to half the standard video frame rate. Simple calibration methods using planar patterns of parallel lines are presented.>
Tsutomu Ito, Daniel DeMenthon, Larry Davis 0001
ICRA1