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This paper describes a pedestrian detection method using a LRF and a small omni-view camera. In outdoor environment, the resolutions of LRFs are too low to recognize human reliably, and high resolution image requires high calculation cost for detecting walking persons. We propose a combination approach using these data. Particle filter based tracking and HOG (Histogram of Oriented Gradients) feature...
With the research and development of chess robot and machine vision, chess robot with visual function has recently received an increasing interest in the community. This paper introduces the chess system of dual-robot coordination based on vision and the process of visual system structure, gives the coordinates translation from computer and image coordinates to actual coordinates. And in the process...
This study focuses on the design of an intelligent machine vision and sorting system. The vision system uses an artificial neural network trained to perform recognition. A Bluetooth communication link facilitates communication between the intelligent recognition system and a robot control computer. Image feature vectors are transmitted to the remote control computer for recognition and a robot control...
Finding injured humans is one of the primary goals of any search and rescue operation. The aim of this paper is to address the task of automatically finding people lying on the ground in images taken from the on-board camera of an unmanned aerial vehicle (UAV). In this paper we evaluate various state-of-the-art visual people detection methods in the context of vision based victim detection from an...
We apply our general-purpose algorithm for visual category recognition using bag-of-visual-words and other visual features and fusion of SVM classifiers to the recognition of indoor locations. This is an important application in many emerging fields, such as mobile augmented reality and autonomous robots. We evaluate the proposed method with other location recognition systems in the ImageCLEF 2010...
We present an integrated vision and robotic system that plays, and learns to play, simple physically-instantiated board games that are variants of TIC TAC TOE and HEXA-PAWN. We employ novel custom vision and robotic hardware designed specifically for this learning task. The game rules can be parametrically specified. Two independent computational agents alternate playing the two opponents with the...
This paper is motivated by the real world problem of search and rescue by unmanned aerial vehicles (UAVs). We consider the problem of tracking a static target from a bird's-eye view camera mounted to the underside of a quadrotor UAV. We begin by proposing a target detection algorithm, which we then execute on a collection of video frames acquired from four different experiments. We show how the efficacy...
We aim to perform robust and fast vision-based localization using a pre-existing large map of the scene. A key step in localization is associating the features extracted from the image with the map elements at the current location. Although the problem of data association has greatly benefited from recent advances in appearance-based matching methods, less attention has been paid to the effective...
Robust object detection is a critical skill for robotic applications in complex environments like homes and offices. In this paper we propose a method for using multiple cameras to simultaneously view an object from multiple angles and at high resolutions. We show that our probabilistic method for combining the camera views, which can be used with many choices of single-image object detector, can...
This paper describes an integrated robot system, known as Curious George, that has demonstrated state-of-the-art capabilities to recognize objects in the real world. We describe the capabilities of this system, including: the ability to access web-based training data automatically and in near real-time, the ability to model the visual appearance and 3D shape of a wide variety of object categories,...
Visual servoing, using the visual measurements direct in the control loop, is a problem that in recent years has grown in interest. One of the main problems involved in these systems is that, while the robot manipulator has a well known model and identification methods have been available, the vision system introduces a nonlinear transformation and modifies the dynamics as seen in the image plane...
Mobile robots typically operate in environments where objects of interest are likely to appear as mixtures of colors and textures with complex outlines. To use color or multispectral imagery for identification and decision-making, systems that can quickly be trained by example to recognize such objects have distinct advantages. Two examples are shown of the use of WAY-2C, a system for color-based...
This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effector. This departs from eye-in-hand systems that move the camera while keeping the scene static. Our robot leverages a simple nudge action to obtain the motion segmentation of an object in stereo. The robot uses the segmentation...
The problem of online sampling of data, can be seen as a generalization of the classical secretary problem. The goal is to maximize the probability of picking the k highest scoring samples in our data, making the decision to select or reject a sample online. We present a new and simple online algorithm to optimally make this selection. We then apply this algorithm to a sequence of images taken by...
We describe a navigation and coverage system based on unsupervised learning driven by visual input. Our objective is to allow a robot to remain continuously moving above a terrain of interest using visual feedback to avoid leaving this region. As a particular application domain, we are interested in doing this in open water, but the approach makes few domain-specific assumptions. Specifically, our...
The computation of a mobile robot position and orientation is a common task in the area of computer vision and image processing. For a successful application, it is important that the position and orientation of a mobile robot must be determined properly. In this paper, a simple procedure for determining the orientation of the mobile robot using two cameras is presented. The two cameras are used to...
Natural feature image recognition (NFIR) is camera based robotic vision system for recognition, acquisition, tracking and pose estimation of a target vehicle. This paper presents our on-going work on development of the capability of the NFIR software in recognition and acquisition for autonomous rendezvous and docking. The heart of the acquisition algorithm is a classification-based scheme. Feature...
In this paper, we present a system of patient robot developed with the aim at improving abilities of nursing student's medical treatment, such as injection to vein. We propose to realize variable emotion of patient robot by using chaos orbit of non-linear time-differentiation equation. To evaluate the effectiveness of the robot through actual injection training, we measure heartbeat rate of nurse...
In this paper we study object recognition on a humanoid robotic head. The head is equipped with a stereo vision system with two cameras in each eye, where the cameras have lenses with different view angles. Such a system models the foveated structure of a human eye. To facilitate the pursuit of moving objects, we provide mathematical analysis that enables the robot to guide the narrow-view cameras...
This paper describes the procedure for detection and tracking of a vehicle from an on-road image sequence taken by a monocular video capturing device in real time. The main objective of such a visual tracking system is to closely follow objects in each frame of a video stream, such that the object position as well as other geometric information are always known. In the tracking system described, the...
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