Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 27 for “"object localization"”.
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Object localization in natural images
"Object localization algorithms aim at finding out what objects exist in an image and where each object is. Object localization is fundamental to many computer vision problems. Simply knowing what is in the image is not enough when we want to reason about object properties such as shape, color or …
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Object Localization by Combining Shape and Appearance Features
<p>Object localization is an important task in computer vision, which is usually handled by searching for an optimal subwindow that tightly covers the object of interest. Both boundary-based shape and region-based appearance features are important to accurate object localization. For some objects, …
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Object Localization, Segmentation, and Classification in 3D Images
<p>We address the problem of identifying objects of interest in 3D images as a set of related tasks involving localization of objects within a scene, segmentation of observed object instances from other scene elements, classifying detected objects into semantic categories, and estimating the 3D …
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Underwater object localization using a biomimetic binaural sonar
Thesis (S.M. in Oceanographic Engineering)--Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 1999.
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Learning image enhancement and object localization using evolutionary algorithms
… chain is obtained by applying GP to localize the object of interest in a binary image. Morphology operations use 27 regular structuring elements along with commonly used morphological operations (i.e., erosion, dilation, opening, and closing) to build an optimal MM chain. The obtained chains are …
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Object localization and identification for autonomous operation of surface marine vehicles
… video stream is utilized as input to achieve object localization and identification by application of state-of-the-art Machine Learning algorithms. In particular, deep Convolutional Neural Networks are first trained offline using a collection of images of possible objects to be encountered …
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From first contact to close encounters : a developmentally deep perceptual system for a humanoid robot
… humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, …
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Computational Discovery of Hidden Cues in Photographs
… information that can be extracted to localize objects outside the view of the camera and to see around corners. For example, we show that it is possible to look at shadows cast by an object on a table, such as a teapot, and reconstruct an image of the surrounding room. We describe how to …
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VLEO-Bench: A Framework to Evaluate Vision-Language Models for Earth Observation Applications
… their abilities on scene understanding, localization and counting, and change detection tasks. Motivated by real-world applications, our framework includes scenarios like urban monitoring, disaster relief, land use, and conservation. We discover that, although state-of-the-art VLMs like …
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A statistical approach for shadow detection using spatio-temporal contexts
… shadows are often falsely labeled as foreground objects, which may severely degrade the accuracy of object localization and detection. Effective shadow detection is necessary for accurate foreground segmentation, especially for outdoor scenes. Based on the characteristics of shadows, such as …
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Development of an AI-driven robotic manipulation framework
… capabilities of the system rely on YOLOv7 for object detection, Semi-Global Block Matching (SGBM) for object localization, and Principal Component Analysis (PCA) for object orientation. Moreover, MoveIt is utilized for motion planning, and the simulation environment is powered by Gazebo. These …
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Fusion of Frequency and Spatial Domain Information for Motion Analysis
… of interest are finding the number of moving objects, velocity estimation, object tracking, and motion segmentation. The proposed hybrid approach performs the motion estimation based on frequency-domain information, but also uses spatial information for precise object localization. Unlike …
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Feedback convolutional neural network in applications of computer vision
… approach to derive a measurement of “objectness,” which is further used as region proposal for object detection, and semantic segmentation. Motivated by the “biased competition theory,” which states that 1) a visual task is highly driven by goal or task, and 2) the unrelated neuron …
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Visual attention in primates and for machines - neuronal mechanisms
… multiple neurophysiological effects, real-world object localization, and a visual masking paradigm (OSM). In each of the considered fields, the work also advances the current state-of-the-art to better understand this aspect of attention itself. The three chosen aspects highlight that the …
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3D model-based pose estimation of rigid objects from a single image for robotics
… problem of finding the best 3D pose for a known object, supported on a horizontal plane, in a cluttered scene in which the object is not significantly occluded. We assume that we are operating with RGB-D images and some information about the pose of the camera. We also assume that a 3D mesh model …
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Cooperative Perception in Autonomous Ground Vehicles using a Mobile Robot Testbed
… down into sub-tasks of cooperative relative localization and map merging. Cooperative relative localization is achieved using visual and inertial sensors, where a computer-vision based camera relative pose estimation technique, augmented with position information, is used to provide a …
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Weakly supervised learning from referring expression: Challenge and directions
… fully supervised semantic segmentation of object recognition tasks, in which a a small set of discrete class bases is provided, the referring expression task is performed associated with a sentence phrase, e.g. “the dude on the dolphin”. Previous approaches use LSTM and fully convolutional …
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General-Purpose Task Guidance from Natural Language in Augmented Reality using Vision-Language Models
… for use, require CAD models of real-world objects, or only function for limited types of tasks or environments. We propose a general-purpose AR task guidance approach and proof-of-concept system to generate guidance for tasks defined by natural language. Our approach allows an operator to …
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Computer vision for railroad track inspection
… due to its potential to improve the efficiency, objectivity, and accuracy when analyzing large databases of acquired video and images. We utilize those promising results to develop a more general method to detect and segment any periodically occurring objects in an image. The techniques used to …
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A model generalization study in localizing indoor cows with cow localization (colo) dataset
… farming increasingly relies on advanced object localization techniques to monitor livestock health and optimize resource management. In recent years, computer vision-based localization methods have been widely used for animal localization. However, certain challenges still make the task …
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