Point Matching as a Classification Problem for Fast and Robust Object Pose Estimation
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We present a data-driven approach to discover different styles that people use to present themselves in online video blogging (vlogging). By vlogging style, we denote the combination of conscious and unconscious choices that the vlogger made during the pro ...
This paper introduces an area- and power-efficient approach for compressive recording of cortical signals used in an implantable system prior to transmission. Recent research on compressive sensing has shown promising results for sub-Nyquist sampling of sp ...
Achieving perfect scale-invariance is usually not possible using classical color image features. This is mostly because of the fact that a traditional image is a two-dimensional projection of the real world. In contrast, light field imaging makes available ...
International Society for Optics and Photonics2014
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...
École Polytechnique Fédérale de Lausanne (EPFL)2014
In this work a new method for automatic image classification is proposed. It relies on a compact representation of images using sets of sparse binary features. This work first evaluates the Fast Retina Keypoint binary descriptor and proposes imp ...
This thesis proposes a novel unified boosting framework. We apply this framework to the several face processing tasks, face detection, facial feature localisation, and pose classification, and use the same boosting algorithm and the same pool of features ( ...
Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...
Programme doctoral en Informatique, Communications et Information2013
We propose a 6D RGB-D odometry approach that finds the relative camera pose between consecutive RGB-D frames by keypoint extraction and feature matching both on the RGB and depth image planes. Furthermore, we feed the estimated pose to the highly accurate ...
In many 3-D object-detection and pose-estimation problems, run-time performance is of critical importance. However, there usually is time to train the system. We introduce an approach that takes advantage of this fact by formulating wide-baseline matching ...