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This paper proposes a global image representation based on Locality-constrained Linear Coding (LLC), with an aim to simplify the encoding process of local descriptors so as to facilitate large-scale image retrieval. Starting from the state-of-the-art Fisher Vector (FV) representation, we replace the computation of sophisticated posterior probabilities with simpler LLC. We then conduct several empirical...
This paper investigates coverage control for visual sensor networks based on gradient descent techniques on matrix manifolds. We consider the scenario that networked vision sensors with controllable orientations are distributed over 3-D space to monitor 2-D environment. Then, the decision variable must be constrained on the Lie group SO(3). The contribution of this paper is two folds. The first one...
Spatial variability in intrinsic brain networks has not been well studied in fMRI. Independent vector analysis (IVA), is a blind source separation approach that can be used for segregating fMRI data into temporally coherent, maximally spatially independent networks enabling comparison among subjects similar to group independent component analysis (GICA). Using simulated and small sample real data,...
State estimation for Micro Air Vehicles (MAVs) is challenging because sensing instrumentation carried on-board is severely limited by weight and power constraints. In addition, their use close to and inside structures and vegetation means that GPS signals can be degraded or all together absent. Here we present a navigation system suited for use on MAVs that seamlessly fuses any combination of GPS,...
Accessing the visual information of video content is a challenging task. Automatic annotation techniques have made significant progress, however they still suffer from the lack of appropriate training data. To overcome this problem we propose the use of still images taken from a photo sharing website as an additional resource for training. However, a mere extension of the training set with still images...
This paper addresses the problem of image annotation using a combination of visual and semantic information. Our model involves two stages: a Nearest Neighbor computation and a tag transfer stage that collects the final annotations. For the latter stage, several algorithms have been implemented in the past using labels' information or including implicitly some visual features. In this paper we propose...
Assessments of functional connectivity between brain networks is a fixture of resting state fMRI research. Until very recently most of this work proceeded from an assumption of stationarity in resting state network connectivity. In the last few years however, interest in moving beyond this simplifying assumption has grown considerably. Applying group temporal independent component analysis (tICA)...
Nowadays, the stereoscopic 3D (S3D) has become more and more popular. However, sometimes people can still feel uncomfort when watching S3D videos. This phenomenon, to some extent, comes from the non-synchronization of the left and right views. That is, when a S3D videos is shot by two individual cameras, the left frames can't match exactly with their corresponding right frames in time domain. If the...
Modern fleet management systems typically monitor the status of hundreds of vehicles by relying on GPS and other simple sensors. Such systems experience significant problems in cases of GPS glitches as well as in areas without GPS coverage. Additionally, when the tracked vehicle is stationary, they cannot discriminate between traffic jams, service stations, parking lots, serious accidents and other...
In this paper, we focus on generating compact but efficient video signatures on mobile devices so that users quickly know whether there are near-duplicates in the social network systems when they upload a video. For this, the proposed method employs the idea of inverted index that is one of the most popular text retrieval methods. Experimental results show that our method can achieve similar results...
In this paper, a new visual SLAM system which incorporates the structure information of the environment is proposed. The proposed system incrementally builds the map data and extracts structure information from the map points using a clustering method. The extracted prior structure is then embedded in the system by means of a new representation of the structure together with the corresponding map...
For the past few years, the performance of object recognition and retrieval has been substantially boosted, which is largely attributed to the advent of many effective image descriptors. The most representative examples are the Fisher Vector (FV) and the Vector of Locally Aggregated Descriptors (VLAD). In this paper we focus on the latter. The original VLAD descriptor directly accumulates the sums...
In this paper, model predictive controller for the visual servo steering of a mobile robot in polar coordinate is presented. Firstly, a kinematic predictive steering controller utilized to generate the command of velocity is introduced. Then, a dynamic predictive controller is designed to steer the system. The model predictive control (MPC) can deal with the constraints easily and it can be iteratively...
We consider the problem of bearing-based visual homing: Given a mobile robot which can measure bearing directions corresponding to known landmarks, the goal is to guide the robot toward a desired “home” location. We propose a control law based on the gradient field of a Lyapunov function, and give sufficient conditions for global convergence. We show that the well-known Average Landmark Vector method...
This paper proposes a vision-based target following and landing system for a quadrotor vehicle on a moving platform. The system is consisted with vision-based landing site detection and locating algorithm using an omnidirectional lens. Latest smartphone was attached on the UAV and served as an on-board image acquisition and process unit. Measurements from the omnidirectional camera are combined with...
Visualization of complex real-world data is an essential part of network processing. Complex high-dimensional or networked data ought to be presented in a form suitable for machine and human analysis. Therefore, advanced methods of dimension reduction or projection to low-dimensional spaces are investigated. In this work we use Differential Evolution as a real-parameter optimization metaheuristic...
We address the problem of sound representation and classification and present results of a comparative study in the context of a domestic robotic scenario. A dataset of sounds was recorded in realistic conditions (background noise, presence of several sound sources, reverberations, etc.) using the humanoid robot NAO. An extended benchmark is carried out to test a variety of representations combined...
This paper proposes a novel set-point control method of a musculoskeletal system by combining a feedforward and feedback manner to complement each drawback each other. In our previous work, a feedforward positioning method of the musculoskeletal arm model was proposed which does not need any realtime sensory information. Its performance, however, depends on a muscular arrangement and an attitude of...
This paper proposes a framework for learning human-provided category labels that describe individual objects, pairwise object relationships, as well as groups of objects. The framework was evaluated using an experiment in which the robot interactively explored 36 objects that varied by color, weight, and contents. The proposed method allowed the robot not only to learn categories describing individual...
This paper introduces a novel approach to topo-logical place detection. The approach is based on previously proposed bubble space representation — where all sensory features and their relative S2- geometry are encoded in a manner that is implicitly dependent on robot pose. Its novelty is that ensuring sensory data reliability is integrated with place detection. This is achieved via checking for informativeness,...
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