2,694 research outputs found
Discovering Regularity in Point Clouds of Urban Scenes
Despite the apparent chaos of the urban environment, cities are actually replete with regularity. From the grid of streets laid out over the earth, to the lattice of windows thrown up into the sky, periodic regularity abounds in the urban scene. Just as salient, though less uniform, are the self-similar branching patterns of trees and vegetation that line streets and fill parks. We propose novel methods for discovering these regularities in 3D range scans acquired by a time-of-flight laser sensor. The applications of this regularity information are broad, and we present two original algorithms. The first exploits the efficiency of the Fourier transform for the real-time detection of periodicity in building facades. Periodic regularity is discovered online by doing a plane sweep across the scene and analyzing the frequency space of each column in the sweep. The simplicity and online nature of this algorithm allow it to be embedded in scanner hardware, making periodicity detection a built-in feature of future 3D cameras. We demonstrate the usefulness of periodicity in view registration, compression, segmentation, and facade reconstruction. The second algorithm leverages the hierarchical decomposition and locality in space of the wavelet transform to find stochastic parameters for procedural models that succinctly describe vegetation. These procedural models facilitate the generation of virtual worlds for architecture, gaming, and augmented reality. The self-similarity of vegetation can be inferred using multi-resolution analysis to discover the underlying branching patterns. We present a unified framework of these tools, enabling the modeling, transmission, and compression of high-resolution, accurate, and immersive 3D images
Smart environment monitoring through micro unmanned aerial vehicles
In recent years, the improvements of small-scale Unmanned Aerial Vehicles (UAVs) in terms of flight time, automatic control, and remote transmission are promoting the development of a wide range of practical applications. In aerial video surveillance, the monitoring of broad areas still has many challenges due to the achievement of different tasks in real-time, including mosaicking, change detection, and object detection. In this thesis work, a small-scale UAV based vision system to maintain regular surveillance over target areas is proposed. The system works in two modes. The first mode allows to monitor an area of interest by performing several flights. During the first flight, it creates an incremental geo-referenced mosaic of an area of interest and classifies all the known elements (e.g., persons) found on the ground by an improved Faster R-CNN architecture previously trained. In subsequent reconnaissance flights, the system searches for any changes (e.g., disappearance of persons) that may occur in the mosaic by a histogram equalization and RGB-Local Binary Pattern (RGB-LBP) based algorithm. If present, the mosaic is updated. The second mode, allows to perform a real-time classification by using, again, our improved Faster R-CNN model, useful for time-critical operations. Thanks to different design features, the system works in real-time and performs mosaicking and change detection tasks at low-altitude, thus allowing the classification even of small objects. The proposed system was tested by using the whole set of challenging video sequences contained in the UAV Mosaicking and Change Detection (UMCD) dataset and other public datasets. The evaluation of the system by well-known performance metrics has shown remarkable results in terms of mosaic creation and updating, as well as in terms of change detection and object detection
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
Curve-Based Shape Matching Methods and Applications
One of the main cues we use in our everyday life when interacting with the environment is shape.
For example, we use shape information to recognise a chair, grasp a cup, perceive traffic signs and
solve jigsaw puzzles. We also use shape when dealing with more sophisticated tasks, such as the
medical diagnosis of radiographs or the restoration of archaeological artifacts. While the perception
of shape and its use is a natural ability of human beings, endowing machines with such skills is
not straightforward. However, the exploitation of shape cues is important for the development of
competent computer methods that will automatically perform tasks such as those just mentioned.
With this aim, the present work proposes computer methods which use shape to tackle two important
tasks, namely packing and object recognition.
The packing problem arises in a variety of applications in industry, where the placement of a set
of two-dimensional shapes on a surface such that no shapes overlap and the uncovered surface area
is minimised is important. Given that this problem is NP-complete, we propose a heuristic method
which searches for a solution of good quality, though not necessarily the optimal one, within a reasonable
computation time. The proposed method adopts a pictorial representation and employs a greedy
algorithm which uses a shape matching module in order to dynamically select the order and the pose
of the parts to be placed based on the “gaps” appearing in the layout during the execution.
This thesis further investigates shape matching in the context of object recognition and first considers
the case where the target object and the input scene are represented by their silhouettes. Two distinct
methods are proposed; the first method follows a local string matching approach, while the second
one adopts a global optimisation approach using dynamic programming. Their use of silhouettes,
however, rules out the consideration of any internal contours that might appear in the input scene,
and in order to address this limitation, we later propose a graph-based scheme that performs shape
matching incorporating information from both internal and external contours. Finally, we lift the assumption
made that input data are available in the form of closed curves, and present a method which
can robustly perform object recognition using curve fragments (edges) as input evidence. Experiments
conducted with synthetic and real images, involving rigid and deformable objects, show the
robustness of the proposed methods with respect to geometrical transformations, heavy clutter and
substantial occlusion
Robotic Assembly Using 3D and 2D Computer Vision
The content of this thesis concerns the development and evaluation of a robotic cell used for
automated assembly. The automated assembly is made possible by a combination of an eye-inhand
2D camera and a stationary 3D camera used to automatically detect objects. Computer
vision, kinematics and programming is the main topics of the thesis. Possible approaches to
object detection has been investigated and evaluated in terms of performance. The kinematic
relation between the cameras in the robotic cell and robotic manipulator movements has been
described. A functioning solution has been implemented in the robotic cell at the Department
of Production and Quality Engineering laboratory.
Theory with significant importance to the developed solution is presented. The methods used
to achieve each part of the solution is anchored in theory and presented with the decisions and guidelines made throughout the project work in order to achieve the final solution.
Each part of the system is presented with associated results. The combination of these results yields a solution which proves that the methods developed to achieve automated assembly works as intended. Limitations, challenges and future possibilities and improvements for the solution is then discussed.
The results from the experiments presented in this thesis demonstrates the performance of the
developed system. The system fulfills the specifications defined in the problem description and is functioning as intended considering the instrumentation used
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