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In many scenarios, domestic robot will regularly encounter unknown objects. In such cases, top-down knowledge about the object for detection, recognition, and classification cannot be used. To learn about the object, or to be able to grasp it, bottom-up object segmentation is an important competence for the robot. Also when there is top-down knowledge, prior segmentation of the object can improve...
This paper presents a scheme which takes as input a 3D point cloud and an associated color image and parses the scene into a collection of salient planar surfaces. The scheme makes use of a fast color segmentation scheme to divide the color image into coherent regions and the groupings suggested by this procedure are used to inform and accelerate a RANSAC based interpretation process. Results on real...
This paper presents a novel approach for floor obstacle segmentation in omnidirectional images which rests upon the fusion of multiple classification generated from heterogeneous segmentation schemes. The individual naive Bayes classifiers rely on different features and cues to determine a pixel's class label. Ground truth data for training and testing the classifiers is obtained from the superposition...
While the use of naturally-occurring features is a central focus of machine perception, artificial features (fiducials) play an important role in creating controllable experiments, ground truthing, and in simplifying the development of systems where perception is not the central objective. We describe a new visual fiducial system that uses a 2D bar code style “tag”, allowing full 6 DOF localization...
While the arctic possesses significant information of scientific value, surprisingly little work has focused on developing robotic systems to collect this data. For arctic robotic data collection to be a viable solution, a method for navigating in the arctic, and thus of assessing glacial terrain, must be developed. Segmenting the ground plane from the rest of the image is one common aspect of a visual...
In order to overcome the instability of the lane object recognition based on only one feature, the shadiness object is extracted from the lane image, multi-features information including texture and edge are adopted, Eigen vectors composing of texture and edge are transformed with fuzzy theory to subjection degree and fuzzy density. Finally, they are fused with fuzzy rules in the frame of particle...
In this paper, a new algorithm is proposed to segment medical images to extract the contour of the objects. First, do edge segmentation to the image region with Prewitt operator. And then use Hough transformation to detect the incontinuous points in curve and link the edges. An accurate edge of the organ or tissue of human can be extracted through this method. Based on this, more information can be...
The soccer robot assembly system belongs to the intelligence robot assembly system, this article take the YSU soccer robot assembly system as a platform, proposed unifies the auto-adapted threshold value method based on HIS and RGB, improved in the original system in the multi-objective search process image to gather slow and the robust bad situation.
In this paper a visual self-localization method for a humanoid robot is presented. This one is based on monocular information. The goal of this method is to obtain the position (x; y) and orientation θ of the humanoid robot inside the field of play. The methods proposed include some digital image processing algorithms and geometric interpretation to perform a 3D monocular reconstruction, that allows...
In this paper, we proposed a novel laser line detection method for robot applications using laser scan line. The method is a robust algorithm dealing with many challenges of line detection, particularly in laser line detection, such as the saturation phenomenon of laser light, the effects of white ambient light and the segmentation of laser scan line caused by obstacles. First, the method takes advantages...
This paper presents a real-time and autonomous algorithm for generating low-complexity multi-planar 3D models of indoor environments with a mobile robot equipped with range finders and a panoramic camera. In contrast with previous studies, our algorithm relies on neither iterative computations nor manual processing but, instead, is incremental online. At each time step, a line of range finder measurements...
In robotics, it is a common problem that for a given task many algorithms are available. For a particular environmental context and some computational constraints some algorithms will perform better and others will perform worse. Consequently, a robot, evolving in a real world environment where both the context and the constraints change in real time, should be able to select in real time algorithms...
A 2D polygons recognition method is proposed. First, a polygonal vertex detection is applied and the two strongest guesses are retained. Then a polygonal fitting algorithm using as input the two vertices and the object contour provides a precise object identification and description. A software environment was designed to test and use the proposed method, and to evaluate its speed and accuracy. The...
Fingerprint image quality estimation is crucial in eliminating poor fingerprint images, which will affect the performance of the automatic fingerprint identification system. In this paper, we present an image quality estimation method based on neural network. Unlike other methods, which are also based on neural network, we directly take the gray value of fingerprints as inputs into the network. This...
This paper focuses on the fast and automatic detection and segmentation of unknown objects in unknown environments. Many existing object detection and segmentation methods assume prior knowledge about the object or human interference. However, an autonomous system operating in the real world will often be confronted with previously unseen objects. To solve this problem, we propose a segmentation approach...
Real-time and accurate image matching is a key to stereo vision of agricultural harvesting robots. This research is part of a pineapple harvesting robot project. In this paper, pineapples were selected as research objects and low cost binocular vision platform was constructed, fruit area of left image was got by real-time image acquisition and rapid segmentation, rapid matching of fruit area in left...
Hand posture classification is a key problem for many human computer interaction applications. However, this is not a simple problem. In this paper, we propose to decompose the hand posture classification problem into 2 steps. In the first step, we detect skin regions using a very fast algorithm of color segmentation based on thresholding technique. This segmentation is robust to lighting condition...
In this paper we present a method for learning new objects situated in uncontrolled and unstructured environments. Visual information only is usually not sufficient for a reliable segmentation and learning of unknown objects without any a priori information. We propose an approach in which the robot introduces additional information by manipulating the entities in the scene, thus generating sufficient...
This paper describes a vision-based ground-plane classification system for autonomous indoor mobile-robot that takes advantage of the synergy in combining together multiple visual-cues. A priori knowledge of the environment is important in many biological systems, in parallel with their reactive systems. As such, a learning model approach is taken here for the classification of the ground/object space,...
Object identification is closely related to the mechanism of extracting the exact object from the robots memory location. Generally, a large number of algorithms and techniques are available to perform the object storage classification and the extraction. Each and everyone work its own style to perform the desired operation they were initiated by the external process. In this algorithm, we focus on...
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