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This paper incorporates sampling-based global path planning with model predictive image-based visual servoing (IBVS) for quadrotor unmanned aerial vehicles (UAVs) equipped with a fixed camera. The proposed method produces safe control inputs of quadrotor in obstacle environment by taking image feature kinematics into account. Firstly, we utilize a sampling-based algorithm for optimal path planning,...
In recent years, both online retail and video hosting service have been exponentially grown. In this paper, a novel deep neural network, called AsymNet, is proposed to explore a new cross-domain task, Video2Shop, targeting for matching clothes appeared in videos to the exactly same items in online shops. For the image side, well-established methods are used to detect and extract features for clothing...
In view of the characteristics of non-silicon flat micro parts in MEMS devices, such as small, light and thin, a vacuum adsorption microassembly system based on microvision was established. Through the research on the key assembly technologies of micro-gripper operation, moving control and micro vision positioning, a general scheme of automatic assembly for flat micro parts is put forward, which is...
Robotic graspable object recognition is a crucial ingredient in many exciting autonomous manipulation applications. However, identifying complex image features from limited data remains largely unsolved. In this paper, we leverage the advantages of two kinds of feature representation approaches, kernel descriptors and deep neural networks, to present a novel hierarchical feature learning framework...
In view of the assembly process characteristic of non-silicon flat micro parts in MEMS devices, a micro assembly control system is developed based on an established experimental platform. According to the characteristics of the micro parts, micro parts recognition and positioning method is studied, and a new matching algorithm based on shape template is proposed, then an identification module has...
In this paper, we propose a method for improving the maneuverability of master-slave systems. We aim at reproducing human skillfulness and dynamic performance in master-slave robots by using assist control for human operators. In this paper, we tackle a reaching task performed by a master-slave robot and propose an operation assist algorithm based on visual feedback control. The algorithm consists...
In the paper, we propose a method for improving maneuverability of master-slave systems. We aim for reproducing human skillfulness and dynamic performance in master-slave robots by using assist control for human operators. In this paper, we focus on a reaching task of a master-slave robot and propose an operation assist algorithm based on visual feedback control. It consists of visual recognition...
Region-based Image Retrieval (RBIR), which bases itself on image segmentation rather than global features or key-point-based local features, is a branch of Content-based Image Retrieval. This paper proposes a novel RBIR-oriented image segmentation algorithm named Edge Integrated Minimum Spanning Tree (EI-MST). The difference between EI-MST and the traditional MST-based methods is that EI-MST generates...
In recent years, the demand for robots that can perform various tasks in dangerous environments has increased. Teleoperated robots are more suitable for dangerous environments than autonomous robots. We have developed a master-slave robot system that consists of a lightweight master device and a high-power slave robot and proposed operation assistance methods to improve the dexterity and increase...
Along with the arrival of multimedia time, multimedia data has replaced textual data to transfer information in various fields. As an important form of multimedia data, images have been widely utilized by many applications, such as face recognition and image classification. Therefore, how to accurately annotate each image from a large set of images is of vital importance but challenging. To perform...
Cell nucleation and premature cell growth in extrusion foaming are critical to elaborate the morphology of final foams. These courses happen in the extrusion die which has been unknown for real extrusion foaming process. In this study, a novel visualization system was developed to online observe the cell nucleation and evolution behavior in the extrusion die. The cell evolution and real time pressure...
A simple and reliable keypoint matching method is proposed in this paper. Our research is motivated by the desire to improve the performance of multi-view geometry (MVG) based verification in visual loop closure detection under significant illumination change, where traditional methods may fail due to their inability to either find a sufficient number of correctly matched keypoints or identify correct...
Deep learning technologies have been successfully applied to acoustic emotion recognition lately. In this work, we propose to apply multi-task learning for acoustic emotion recognition based on the Deep Belief Network (DBN) framework. We treat the categorical emotion recognition task as the major task. For the secondary task, we leverage two continuous labels, valence and activation. Two strategies...
The propagation and influence is an important problem for online social network. In this paper, we develop a visualization toolkit for online social network propagation and influence analysis and predication which can not only present the main trend of the propagation and influence, but also can present them in multiple views e.g., time and location distribution. Considering the existing works mostly...
Stochastic model checking is using the verification method of model checking to quantitative verification system model with stochastic behaviours. In recent years, stochastic model checking make a great advancement. In this paper, the high level system model PPN is extended with label, and is used to as the formal model for system with stochastic behaviours; PCTL∗ is selected to as the property specification,...
We propose an online robust object tracking algorithm based on a sample-based dictionary. The sample-based dictionary in our method means that the over-completely dictionary of sparse coding algorithm is formed by using the sample basis extracted from video images. Different from the other tracking methods that use the object features and a set of boosted classifiers, the proposed algorithm considers...
We present the performance evaluation of different whole-image descriptors in visual loop closure detection. A whole-image descriptor here is defined as the one that does not require keypoint detection and is therefore fast to extract. In addition, it can be extremely compact to reduce storage requirement. This type of image descriptors are attracting an increasing amount of interest in appearance-based...
This work addresses the problem of constructing an effective training set at minimal labeling cost by selecting some images to build a subset from the whole database. This problem occurs in situations that the number of categories is large or the cost of obtaining labeled images is extremely high, because the images selected by uniform sampling do not reflect the desired training distribution and...
With the permeation of Web 2.0, large-scale user contributed images with tags are easily available on social websites. How to align these social tags with image regions is a challenging task while no additional human intervention is considered, but a valuable one since the alignment can provide more detailed image semantic information and improve the accuracy of image retrieval. To this end, we propose...
We propose a simple and effective method for visual loop closure detection in appearance-based robot SLAM. Unlike the Bag-of-Words (BoW hereafter) approach in most existing work of the problem, our method uses direct feature matching to detect loop closures and therefore avoid the perceptual aliasing problem caused by the vector quantization process of BoW. We show that a tree structure can be efficient...
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