This work presents a geometry based vision system for aircraft recognition and pose estimation using single images. Pose estimation improves the tracking performance of guided weapons with imaging seekers, and is useful in estimating target manoeuvres and aim-point selection required in the terminal phase of missile engagements. After edge detection and straight-line extraction, a hierarchy of ...

Cameras provide only bi-dimensional views of three-dimensional objects. These views are projections that change depending on the spatial orientation or pose of the object. In this paper we propose a technique to estimate the pose of a 3D object knowing only a 2D picture of it. The proposed technique explores both the linear and the nonlinear composite correlation filters in a combination with a...

This paper introduces our head pose estimation system that localizes nose-tip of the faces and estimate head poses in studio quality pictures. After the nose-tip in the training data are manually labeled, the appearance variation caused by head pose changes is characterized by tensor model. Given images with unknown head pose and nose-tip location, the nose-tip of the face is localized in a coa...

An approach to multi-view face detection based on head pose estimation is presented in this paper. Support Vector Regression is employed to solve the problem of pose estimation. Three methods, the eigenface method, the Support Vector Machine (SVM) based method, and a combination of the two methods, are investigated. The eigenface method, which seeks to estimate the overall probability distribut...

Estimating the pose of a camera is a core problem in many geometric vision applications. While there has been much progress in the last two decades, the main difficulty is still dealing with data contaminated by outliers. For many scenes, e.g. with poor lightning conditions or repetitive textures, it is common that most of the correspondences are outliers. For real applications it is therefore ...

In this paper a robust method is presented to classify and estimate an objects pose from a real time range image and a low dimensional model. The model is made from a range image training set which is reduced dimensionally by a nonlinear manifold learning method named Local Linear Embedding (LLE). New range images are then projected to this model giving the low dimensional coordinates of the ob...

In this paper we present an improved color based planar fiducial marker system. Our framework provides precise and robust full 3D pose estimation of markers with superior accuracy when compared with many fiducial systems in the literature, while color information encoding enables using over 65,000 distinct markers. Unlike most color-based fiducial frameworks, which requires prior classification...

We present a fast algorithm for face detection and precise pose estimation. Our detection scheme is based on a tree-structured hierarchy of face vs. background classifiers combined with a lazy evaluation strategy which concentrates computation on ambiguous areas of the image. The hierarchy corresponds to successive partitions of the pose parameter space, and thereby provides, at no additional c...

In this paper, we propose a new feature extraction method for regression problems. It is a modified version of linear discriminant analysis (LDA) which is a very successful feature extraction method for classification problems. In the proposed method, the between class and the within class scatter matrices in LDA are modified so that they fit in regression problems. The samples with small diffe...