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In this paper, we propose a new shape decomposition method based on visual perception for shape matching and retrieval which uses the protrusive corners under multiple scales. Our approach composes of a multi-scale shape decomposition procedure and a contour segments matching procedure. Firstly, morphological operations are used for more stable and visual perceptual corners to get the contour segmented...
The popularization of service robots requires that robots are not expensive and can work very well in human daily living environment. Due to lighting condition and/or cluttered background, there are false detections occasionally for landmark-based robot localization with low-cost color camera or infrared sensors. However, traditional frequently used methods, such as Extended Kalman Filter (EKF) and...
In this paper we present a method to detect and localize abnormal events in crowded scene. Most existing methods use the patch of optical flow or human tracking based trajectory as representation for crowd motion, which inevitably suffer from noises. Instead, we propose the employment of a new and efficient feature, short-term trajectory, which represent the motion of the visible and constant part...
Localization is one of the fundamental problems for mobile robots. Hence, there are several related works carried out for both metric and topological localization. In this paper, we present a lightweight technique for on-line robot topological localization in a known indoor environment. This approach is based on the Generalized Voronoi Diagram (GVD). The core task is to build local GVD to match against...
In this paper ceiling affixed ARToolKitPlus 2D code artificial landmarks are evaluated for purposes of robot localization and navigation. Ceiling affixed codes rarely come in contact with people, equipment or robots, and for this reason they are more likely to stay detectable over a longer period of time. Multi threshold averaging, light gradient compensation and neighbourhood search techniques further...
This paper presents a method to evaluate the attitude of a rigid body under condition of high non-gravitational acceleration. Most of the attitude estimation algorithms based on data from low cost Inertial Measurement Units (IMU), assume that the total acceleration perceived by the accelerometer be gravity or at most small variations of it. When the actual conditions are far away from such assumption,...
In this paper, we present a novel real-time velocity estimation algorithm. A sensor assembly consisting of a monocular camera and an inertial measurement unit with three-axis accelerotmeter and gyroscope is considered. To improve the robustness of the velocity estimator with respective to image noise, we apply a coarse-to-fine structure based on multiple feature correspondences over three consecutive...
It's a natural and convenient way for a robot to interact with outside by robot's ears (i.e. microphones) based on correctly detection and recognition of a sound event. This paper considers sound event detection and recognition in indoor environment where there are varying noises around a robot. To handle the problem of varying background noises, a novel sound event detection and recognition system...
Motion detection is foundation of service robot vision in Human-Robot Interaction (HRI). Foreground detection is an important step of the motion detection. If the foreground detected is not correct, the motion detected will be wrong. To improve the efficiency and robustness of motion detection for HRI, a motion detection system for HRI based on image parameters and HRI context (MDIPC system) is proposed,...
The traditional triangulation algorithms in multiview geometry problems have the drawback that its solution is locally optimal. Robust Optimization is a specific and relatively novel methodology for handling optimization problems with uncertain data. The key idea of robust optimization is to find the best possible performance in the worst case. In this paper, we propose a novel approach which solves...
In this paper, we describe a novel and effective single image enhancement algorithm for haze image. As we observe that, the contrast and intensity of haze image after using dark channel prior approach will unavoidably tend to be lower than those of the real scene, we proposed a method using histogram specification to make an improvement on image after dark channel prior approach. We make a large number...
A new active vision based lane markings recognition approach is presented. An efficient method for separating road surface data from a 3D LIDAR data frame is proposed which delimitates the drivable region by its profile. A new approach for extracting significant points of lane markings is developed using digital signal processing technology. And the significant points are clustered based on an orientation...
A simple interval type-2 fuzzy gain scheduling controller is designed for the stabilization and reference tracking of ball and plate system. The controller employs plate angles as the premise variables for gain scheduling and its stability is guaranteed through a set of linear matrix inequalities. MATLAB simulations are performed to validate the proposed controller where it is also compared with pole...
Adaptive Kalman filter algorithm (AKF) is utilized to improve the performance of the robot's speed and heading angle, which can eliminate the system state noise and error, generated by the sudden change of formation in the multi-robot leader-follower system. The approach guarantees that the robots can reach the desired position quickly and accurately and keep a predetermined formation. The motion...
Automatic power line recognition from cluttered background is an important and challenging task for a vision based unmanned aerial vehicles (UAVs) power line inspection system. In this paper, we propose a power line recognition method based on liner object enhancement and parallel lines constraint. A new double-side filter is proposed to enhance the power lines, and then the radon transform is used...
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