Select All | Select None
Login failed. Please try again.
Forgot your password?
Log in with Facebook
Log in with Google
You can now keep track of new articles from Computer Vision and Image Understanding on your personalized homepage!
In this paper, we present a new graph-based frame work for collaborative place, object, and part recognition in indoor environments. We consider a scene to be an undirected graphical model composed of a place node, object nodes, and part nodes with undirected links. Our key contribution is the...
This paper presents a new robot-vision system architecture for real-time moving object localization. The 6-DOF (3 translation and 3 rotation) motion of the objects is detected and tracked accurately in clutter using a model-based approach without information of the objects’ initial positions....
In this work we propose a probabilistic model for generic object classification from raw range images. Our approach supports a validation process in which classes are verified using a functional class graph in which functional parts and their realization hypotheses are explored. The validation...
In this paper, we propose a novel method for shape analysis that is suitable for any multi-dimensional data set that can be modelled as a manifold. The descriptor is obtained for any pair ( M , ϕ ), where M is a closed smooth manifold and ϕ is a Morse function defined on M . More precisely, we...
results per page
Save this article to read later. You can see your Read Later on your DeepDyve homepage.
To save an article, log in first, or sign up for a DeepDyve account if you don't already have one.
Sign Up Log In
To subscribe to email alerts, please log in first, or sign up for a DeepDyve account if you don't already have one.
Read and print from thousands of top scholarly journals.
Sign up with Facebook
Sign up with Google
Already have an account? Log in
To get new article updates from a journal on your personalized homepage, please log in first, or sign up for a DeepDyve account if you don't already have one.