An ecologically valid reference frame for perspective invariant action recognition

Name: An ecologically valid reference frame for perspective invariant action recognition
Author: Bayram, Berkay, Uğur, E., Asada, M., Öztop, Erhan

İsim	An ecologically valid reference frame for perspective invariant action recognition
Yazar	Bayram, Berkay, Uğur, E., Asada, M., Öztop, Erhan
Basım Tarihi:	2021
Basım Yeri	- IEEE
Konu	Mirror neurons, Perspective invariant action recognition, Reference frame, Robotics
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2-s2.0-85114558481
Kayıt Numarası	b7a3c53a-992c-46b9-8ec6-64ce47503080
Lokasyon	Computer Science
Tarih	2021
Notlar	Ozyegin University ; Tokyo Robotics Inc. ; Osaka University
Örnek Metin	In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames that the brain uses for interacting with the environment. Coordinate transformations are standard tools in robotics and can facilitate perspective invariant action recognition and action prediction based on observed actions of other agents. Although it is known that human adults can do explicit coordinate transformations, it is not clear whether this capability is used for recognizing and understanding the actions of others. Mirror neurons, found in the ventral premotor cortex of macaque monkeys, seem to undertake action understanding in a perspective invariant way, which may rely on lower level perceptual mechanisms. To this end, in this paper we propose a novel reference frame that is ecologically plausible and can sustain basic action understanding and mirror function. We demonstrate the potential of this representation by simulation of an upper body humanoid robot with an action repertoire consisting of push, poke, move-away and bring-to-mouth actions. The simulation experiments indicate that the representation is suitable for action recognition and effect prediction in a perspective invariant way, and thus can be deployed as an artificial mirror system for robotic applications.
DOI	10.1109/ICDL49984.2021.9515616

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An ecologically valid reference frame for perspective invariant action recognition

Yazar Bayram, Berkay, Uğur, E., Asada, M., Öztop, Erhan

Basım Tarihi 2021

Basım Yeri - IEEE

Konu Mirror neurons, Perspective invariant action recognition, Reference frame, Robotics

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2-s2.0-85114558481

Kayıt Numarası b7a3c53a-992c-46b9-8ec6-64ce47503080

Lokasyon Computer Science

Tarih 2021

Notlar Ozyegin University ; Tokyo Robotics Inc. ; Osaka University

Örnek Metin In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames that the brain uses for interacting with the environment. Coordinate transformations are standard tools in robotics and can facilitate perspective invariant action recognition and action prediction based on observed actions of other agents. Although it is known that human adults can do explicit coordinate transformations, it is not clear whether this capability is used for recognizing and understanding the actions of others. Mirror neurons, found in the ventral premotor cortex of macaque monkeys, seem to undertake action understanding in a perspective invariant way, which may rely on lower level perceptual mechanisms. To this end, in this paper we propose a novel reference frame that is ecologically plausible and can sustain basic action understanding and mirror function. We demonstrate the potential of this representation by simulation of an upper body humanoid robot with an action repertoire consisting of push, poke, move-away and bring-to-mouth actions. The simulation experiments indicate that the representation is suitable for action recognition and effect prediction in a perspective invariant way, and thus can be deployed as an artificial mirror system for robotic applications.

DOI 10.1109/ICDL49984.2021.9515616