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We present a novel pipeline for augmenting a 3D eye-glass mesh into a person's face. While doing so, we take care about the proper fitment of the glass in terms of pupilary distance computed automatically, which is user-friendly in compare to standard marker based approaches. Our method also performs rigid eye-glass temple correction during augmentation followed by tracking to present realistic rendering...
In this paper, we propose a dense approach for 3D rotation estimation between spherical images, which is simultaneously able to recover the large rotations, robust under clutter and small translations. The key idea is to represent the spherical images by 3D shapes of the triangular mesh surfaces based on image intensity signal. This allows to apply the spherical harmonics representation as 3D shape...
A snake-like robot is a hyper-redundant robot. It has flexible movement ability and high stability with low center of gravity. It is very suitable for environment detection in the rugged road or narrow space. In this paper, a 16-DOFs snake robot is composed. It has ten 2-DOFs modular spherical-shape joints. The joints are arranged as the structure of "(Roll-Pitch)-(Roll-Pitch)-", where "(Roll-Pitch)"...
In this work, a simple model is used to characterize the learning behaviour of humans. Based on this model, it is possible to define a similarity measure between two tasks in order to quantify skill generalisation during the learning of simple motor tasks by humans. By fully exploring this similarity measure, a sequence of tasks capable of improving the learning efficiency for both healthy subjects...
In object recognition techniques, specially feature-based methods, a fundamental step is to extract keypoints which are distinct and considerably interesting in the image. There are many different keypoint detectors already available, each with its own specific use and results vary enormously. It is widely agreed that evaluation of feature detectors is important. To our knowledge there is no comparative...
Reducing the grasp candidates for unknown object grasping while maintaining grasp stability is the goal of this paper. In this paper, we propose an efficient and straight forward unknown object grasping method by using concavities of the unknown objects to significantly reduce the grasp candidates. Shortest path concavity is first employed to work out the concavity value for every vertex of the unknown...
In this paper, we introduce the application of generic multi-level Convolutional Neural Networks (CNN) approach into the scene understanding or image parsing task. Given an input image, first, a set of similar images from the training set are retrieved based on global-level CNN feature matching similarities. Then, the input test image and the similar images are overseg-mented into superpixels. Next,...
We describe a technique for object detection that uses a combination of global shape descriptors and local point descriptors. Our system is able to represent pose using a global shape descriptor, rather than the commonly used part based representation. This approach considerably reduces computational complexity and achieves a significant performance improvement on an extensive dataset: CUB-200-2011...
A novel approach for control and motion planning of formations of multiple unmanned micro aerial vehicles (MAVs), also referred to as unmanned aerial vehicles (UAVs) — multirotor helicopters, in cluttered GPS-denied environments is presented in this paper. The proposed method enables autonomously to design complex maneuvers of a compact MAV team in a virtual-leader-follower scheme. The feasibility...
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