Intermodal trains are typically the fastest trains operated by North American freight railroads. It is thus ironic that these trains tend to have the poorest aerodynamic characteristics. Because of constraints imposed...
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This work addresses the problem of human motion analysis in video sequences of a scene observed by a single fixed camera with high perspective effect. The goal of this work is to make a 2D-Model (made of Shape and Sti...
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ISBN:
(纸本)1904410146
This work addresses the problem of human motion analysis in video sequences of a scene observed by a single fixed camera with high perspective effect. The goal of this work is to make a 2D-Model (made of Shape and Stick figure) viewpoint-insensitive and preprocess the input image for removing the perspective effect. We focus our methodology on using the 3D principal directions of man-made environments and also the direction of motion to transform both 2D-Model and input images to a common frontal view (parallel or orthogonal to the direction of motion) before the fitting process. The inverse transformation is then performed on the resulting human features obtaining a segmented silhouette and a pose estimation in the original input image. Preliminary results are very promising since the proposed algorithm is able to locate head and feet with a better precision than previous one.
In this paper, we present a new dichromatic-based method for estimating illuminant chromaticity using a single image. In the proposed method, specular pixels are roughly extracted from an input image and projected int...
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In this paper we propose a novel algorithm to enhance the face video from omni-directional video camera. A two-stage strategy is used. First stage is the noise elimination, realized by iterative MAP update. Naive Baye...
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In this paper we propose a novel algorithm to enhance the face video from omni-directional video camera. A two-stage strategy is used. First stage is the noise elimination, realized by iterative MAP update. Naive Baye...
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In this paper we propose a novel algorithm to enhance the face video from omni-directional video camera. A two-stage strategy is used. First stage is the noise elimination, realized by iterative MAP update. Naive Bayesian criterion is used to model the posterior. The predominant salt and pepper noise introduced by the omni-to-perspective transformation can be removed effectively, while the image details are well preserved. The high frequency component compensation (HFCC) super-resolution algorithm is applied thereafter to remove the blocky effect. Experimental results show that the video quality has a marked improvement.
In earlier work, we developed a fast method for 2-D shape retrieval based on point correspondences of silhouette contours. That method did not assume that the database shapes had class labels. If class label informati...
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In earlier work, we developed a fast method for 2-D shape retrieval based on point correspondences of silhouette contours. That method did not assume that the database shapes had class labels. If class label information is added, then the shape retrieval system can be used for 2-D shape classification. This paper explores this application, by extending our prior shape retrieval method to make use of class labels, and then evaluating its classification accuracy on a large test database containing 70 object classes. The results show that the method is both highly accurate (96.5-99.6%) and fast (< 1 second).
In recent work, we presented a correspondence-based approach for real-time retrieval from databases of 2-D shapes. The system performs with high speed and accuracy relative to other published systems as measured on a ...
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In recent work, we presented a correspondence-based approach for real-time retrieval from databases of 2-D shapes. The system performs with high speed and accuracy relative to other published systems as measured on a widely used benchmark dataset. In this paper, we test the generalization accuracy of the approach;i.e., its ability to correctly retrieve shapes from a shape database when the query shapes are not contained in the database. The experimental results show that the system's accuracy on novel inputs is nearly as high as its accuracy on shapes that are already contained in the database, demonstrating that the approach has good generalization accuracy. This result provides additional support for the use of the proposed approach for shape retrieval and object recognition applications.
The ability to detect shadows Is a critical feature of any Intelligent transportation system (ITS). The Improper handling of shadows can be the cause of erroneous conclusions in traffic analysis. Because vision-based ...
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The goal of this project is to develop a passive vision-based sensing system capable of monitoring an intersection by observing the vehicle and pedestrian flow, and predicting situations that might give rise to accide...
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The goal of this project is to develop a passive vision-based sensing system capable of monitoring an intersection by observing the vehicle and pedestrian flow, and predicting situations that might give rise to accidents. A single camera mounted at an arbitrary position looking at an intersection is used. However, for extended applications multiple cameras will be needed. Some of the key elements are camera calibration, motion tracking, vehicle classification, and predicting collisions. In this paper, we focus on motion tracking. Motion segmentation is performed using an adaptive background model that models each pixel as a mixture of Gaussians. The method used is similar to the Stauffer method for motion segmentation. Tracking of objects is performed by computing the overlap between oriented bounding boxes. The oriented boxes are computed by vector quantization of blobs in the scene. The principal angles computed during vector quantization along with other cues of the object are used for classification of detected entities into vehicles and pedestrians.
In robotics, homing can be defined as that behavior which enables a robot to return to its initial (home) position, after traveling a certain distance along an arbitrary path. Odometry has traditionally been used for ...
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In robotics, homing can be defined as that behavior which enables a robot to return to its initial (home) position, after traveling a certain distance along an arbitrary path. Odometry has traditionally been used for the implementation of such a behavior, but it has been shown to be an unreliable source of information. In this work, a novel method for visual homing is proposed, based on a panoramic camera. As the robot departs from its initial position, it tracks characteristic features of the environment (corners). As soon as homing is activated, the robot selects intermediate target positions on the original path. These intermediate positions (IPs) are then visited sequentially, until the home position is reached. For the robot to move between two consecutive IPs, it is only required to establish correspondence among at least three corners. This correspondence is obtained through a feature tracking mechanism. The proposed homing scheme is based on the extraction of very low-level sensory information, namely the bearing angles of corners, and has been implemented on a robotic platform. Experimental results show that the proposed scheme achieves homing with a remarkable accuracy, which is not affected by the distance travelled by the robot.
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