3D Object Recognition Using Appearance Model Space of Feature Point
نویسندگان
چکیده
منابع مشابه
A novel Local feature descriptor using the Mercator projection for 3D object recognition
Point cloud processing is a rapidly growing research area of computer vision. Introducing of cheap range sensors has made a great interest in the point cloud processing and 3D object recognition. 3D object recognition methods can be divided into two categories: global and local feature-based methods. Global features describe the entire model shape whereas local features encode the neighborhood ...
متن کامل3D Object Recognition Using Unsupervised Feature Extraction
Intrator (1990) proposed a feature extraction method that is related to recent statistical theory (Huber, 1985; Friedman, 1987), and is based on a biologically motivated model of neuronal plasticity (Bienenstock et al., 1982). This method has been recently applied to feature extraction in the context of recognizing 3D objects from single 2D views (Intrator and Gold, 1991). Here we describe expe...
متن کاملAppearance-based object recognition using optimal feature transforms
In this paper we discuss and compare di!erent approaches to appearance-based object recognition and pose estimation. Images are considered as high-dimensional feature vectors which are transformed in various manners: we use di!erent types of non-linear image-to-image transforms composed with linear mappings to reduce the feature dimensions and to beat the curse of dimensionality. The transforms...
متن کاملAppearance-based and Active 3D Object Recognition using Vision
This paper concerns a topics studied by many researchers around the world: 3D object recognition from vision. In our robotics context,an object must be recognized and localized in order to be grasped by a mobile robot equipped with a manipulator arm Mitsubishi PA10-6C: several cameras are mounted on this robot, on a static mast or on the wrist of the arm. The use of such a robot for object reco...
متن کاملAppearance Based 3D Object Recognition Using IPCA-ICA
Fast incremental non Gaussian directional analysis (IPCA-ICA) is proposed as a linear technique for recognition [1]. The basic idea is to compute the principal components as sequence of image vectors incrementally, without estimating the covariance matrix and at the same time transforming these principal components to the independent directions that maximize the non–Gaussianity of the source. I...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: KIPS Transactions on Software and Data Engineering
سال: 2014
ISSN: 2287-5905
DOI: 10.3745/ktsde.2014.3.2.93