TY  - GEN
ID  - cogprints3329
UR  - http://cogprints.org/3329/
A1  - Arsenio, Artur
A1  - Fitzpatrick, Paul
A1  - Kemp, Charles C.
A1  - Metta, Giorgio
Y1  - 2003///
N2  - Object segmentation is a fundamental problem
in computer vision and a powerful resource for
development. This paper presents three embodied approaches to the visual segmentation of objects. Each approach to segmentation is aided
by the presence of a hand or arm in the proximity of the object to be segmented. The first
approach is suitable for a robotic system, where
the robot can use its arm to evoke object motion. The second method operates on a wearable system, viewing the world from a human's
perspective, with instrumentation to help detect
and segment objects that are held in the wearer's
hand. The third method operates when observing
a human teacher, locating periodic motion (finger/arm/object waving or tapping) and using it
as a seed for segmentation. We show that object segmentation can serve as a key resource for
development by demonstrating methods that exploit high-quality object segmentations to develop
both low-level vision capabilities (specialized feature detectors) and high-level vision capabilities
(object recognition and localization).
PB  - Lund University Cognitive Studies
KW  - object segmentation
KW  -  computer vision
KW  -  robotic system
KW  -  wearable system
TI  - The Whole World in Your Hand: Active and Interactive Segmentation
SP  - 49
AV  - public
EP  - 56
ER  -

<script src='https://archive-bar.soton.ac.uk/archive-bar.js'></script>
<script src='https://archive-bar.soton.ac.uk/google-analytics.js'></script>