A Research Platform for Embodied Visual Object Recognition
Year: 2010
Type: article
Abstract: —We present in this paper a research platform for development and evaluation of embodied visual object recognition strategies. The platform uses a stereoscopic peripheral-foveal camera system and a fast pan-tilt unit to perform saliency-based visual search. This is combined with a classification framework based on the bag-of-features paradigm with the aim of targeting, classifying and recog-nising objects. Interaction with the system is done via typed commands and speech synthesis. We also report the current classification performance of the system. I.
Authors: Marcus Wallenberg, Per-Erik Forssén
Institution: Linköping University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W230130919