Shape from periodic texture using the eigenvectors of local affine distortion

This paper shows how the local slant and tilt angles of regularly textured curved surfaces can be estimated directly, without the need for iterative numerical optimization, We work in the frequency domain and measure texture distortion using the affine distortion of the pattern of spectral peaks. The key theoretical contribution is to show that the directions of the eigenvectors of the affine distortion matrices can be used to estimate local slant and tilt angles of tangent planes to curved surfaces. In particular, the leading eigenvector points in the tilt direction. Although not as geometrically transparent, the direction of the second eigenvector can be used to estimate the slant direction. The required affine distortion matrices are computed using the correspondences between spectral peaks, established on the basis of their energy ordering. We apply the method to a variety of real-world and synthetic imagery

Terrain Classification from Body-mounted Cameras during Human Locomotion

Abstract—This paper presents a novel algorithm for terrain type classification based on monocular video captured from the viewpoint of human locomotion. A texture-based algorithm is developed to classify the path ahead into multiple groups that can be used to support terrain classification. Gait is taken into account in two ways. Firstly, for key frame selection, when regions with homogeneous texture characteristics are updated, the fre-quency variations of the textured surface are analysed and used to adaptively define filter coefficients. Secondly, it is incorporated in the parameter estimation process where probabilities of path consistency are employed to improve terrain-type estimation. When tested with multiple classes that directly affect mobility a hard surface, a soft surface and an unwalkable area- our proposed method outperforms existing methods by up to 16%, and also provides improved robustness. Index Terms—texture, classification, recursive filter, terrain classification I

Low-rank Based Algorithms for Rectification, Repetition Detection and De-noising in Urban Images

In this thesis, we aim to solve the problem of automatic image rectification and repeated patterns detection on 2D urban images, using novel low-rank based techniques. Repeated patterns (such as windows, tiles, balconies and doors) are prominent and significant features in urban scenes. Detection of the periodic structures is useful in many applications such as photorealistic 3D reconstruction, 2D-to-3D alignment, facade parsing, city modeling, classification, navigation, visualization in 3D map environments, shape completion, cinematography and 3D games. However both of the image rectification and repeated patterns detection problems are challenging due to scene occlusions, varying illumination, pose variation and sensor noise. Therefore, detection of these repeated patterns becomes very important for city scene analysis. Given a 2D image of urban scene, we automatically rectify a facade image and extract facade textures first. Based on the rectified facade texture, we exploit novel algorithms that extract repeated patterns by using Kronecker product based modeling that is based on a solid theoretical foundation. We have tested our algorithms in a large set of images, which includes building facades from Paris, Hong Kong and New York

Sea Ice Field Analysis Using Machine Vision

Sea ice field analysis has motivation in various areas, such as environmental, logistics or ship maintenance. Among other methods, local ice field analysis from ship-based visual observations are currently done by human volunteers and therefore are liable to human errors and subjective interpretations. The goal of the thesis is to develop and implement a complete process for obtaining dimensions, distribution and concentration of sea-ice floes, which aims at assisting and improving part of the aforementioned visual observations. Such process involves numerous, organized steps which take advantage of techniques from image processing (lens calibration, vignetting removal and orthorectification), robotics (transformation frames) and machine vision (thresholding and texture analysis methods, and morphological operations). An experimental system setup for collecting the required information is provided as well, which includes a machine vision camera for image acquisition, an IMU device for determining the dynamic attitude of the cameras with respect to the world, two GPS sensors providing a redundant positioning and clock data, and a desktop computer used as the main logging platform for all the collected data. Through a number of experiments, the proposed system setup and image analysis methods have proved to provide promising results in pack ice and brash ice conditions, thus encouraging further research on the topic. Further improvements should target the accuracy of ice floes detection, and over and under-segmentation of the detected sea-ice floes

3D Composer: A Software for Micro-composition

The aim of this compositional research project is to find new paradigms of expression and representation of musical information, supported by technology. This may further our understanding of how artistic intention materialises during the production of a musical work. A further aim is to create a software device, which will allow the user to generate, analyse and manipulate abstract musical information within a multi-dimensional environment. The main intent of this software and composition portfolio is to examine the process involved during the development of a compositional tool to verify how transformations applied to the conceptualisation of musical abstraction will affect musical outcome, and demonstrate how this transformational process would be useful in a creative context. This thesis suggests a reflection upon various technological and conceptual aspects within a dynamic multimedia framework. The discussion situates the artistic work of a composer within the technological sphere, and investigates the role of technology and its influences during the creative process. Notions of space are relocated in the scope of a personal compositional direction in order to develop a new framework for musical creation. The author establishes theoretical ramifications and suggests a definition for micro-composition. The main aspect focuses on the ability to establish a direct conceptual link between visual elements and their correlated musical output, ultimately leading to the design of a software called 3D-Composer, a tool for the visualisation of musical information as a means to assist composers to create works within a new methodological and conceptual realm. Of particular importance is the ability to transform musical structures in three-dimensional space, based on the geometric properties of micro-composition. The compositions Six Electroacoustic Studies and Dada 2009 display the use of the software. The formalisation process was derived from a transposition of influences of the early twentieth century avant-garde period, to a contemporary digital studio environment utilising new media and computer technologies for musical expression

Human-Centric Machine Vision

Recently, the algorithms for the processing of the visual information have greatly evolved, providing efficient and effective solutions to cope with the variability and the complexity of real-world environments. These achievements yield to the development of Machine Vision systems that overcome the typical industrial applications, where the environments are controlled and the tasks are very specific, towards the use of innovative solutions to face with everyday needs of people. The Human-Centric Machine Vision can help to solve the problems raised by the needs of our society, e.g. security and safety, health care, medical imaging, and human machine interface. In such applications it is necessary to handle changing, unpredictable and complex situations, and to take care of the presence of humans

Feature-based object tracking in maritime scenes.

A monitoring of presence, location and activity of various objects on the sea is essential for maritime navigation and collision avoidance. Mariners normally rely on two complementary methods of the monitoring: radar and satellite-based aids and human observation. Though radar aids are relatively accurate at long distances, their capability of detecting small, unmanned or non-metallic craft that generally do not reflect radar waves sufficiently enough, is limited. The mariners, therefore, rely in such cases on visual observations. The visual observation is often facilitated by using cameras overlooking the sea that can also provide intensified infra-red images. These systems or nevertheless merely enhance the image and the burden of the tedious and error-prone monitoring task still rests with the operator. This thesis addresses the drawbacks of both methods by presenting a framework consisting of a set of machine vision algorithms that facilitate the monitoring tasks in maritime environment. The framework detects and tracks objects in a sequence of images captured by a camera mounted either on a board of a vessel or on a static platform over-looking the sea. The detection of objects is independent of their appearance and conditions such as weather and time of the day. The output of the framework consists of locations and motions of all detected objects with respect to a fixed point in the scene. All values are estimated in real-world units, i. e. location is expressed in metres and velocity in knots. The consistency of the estimates is maintained by compensating for spurious effects such as vibration of the camera. In addition, the framework continuously checks for predefined events such as collision threats or area intrusions, raising an alarm when any such event occurs. The development and evaluation of the framework is based on sequences captured under conditions corresponding to a designated application. The independence of the detection and tracking on the appearance of the sceneand objects is confirmed by a final cross-validation of the framework on previously unused sequences. Potential applications of the framework in various areas of maritime environment including navigation, security, surveillance and others are outlined. Limitations to the presented framework are identified and possible solutions suggested. The thesis concludes with suggestions to further directions of the research presented

Geometric models for video surveillance in road environments: vehicle tailgating detection

Traffic accidents constitute one of the main causes of death in many countries. Despite the current efforts devoted to mitigate the effects of road incidents, there are still some variables affecting this problem which are not yet under control or regulation. Spain, for instance, still lacks official regulations about especially risky driving behaviours, such as tailgating. In many cases, the rationale behind is that these behaviours are hard or expensive to detect reliably, thus limiting the extent of the automatic detection systems. This paper proposes a method to identify certain elements in road scenarios, define geometric models that allow computing quantitative measures of the scene and, consequently, detect offending driving behaviours. In this work, we have focused on the particular case of study of tailgating detection. However, the proposed geometric models might become the basis of many other useful applications.Ingeniería de Sistemas Audiovisuale

Range estimation and obstacle detection for unmanned aircraft vehicles: a stereo vision approach

The aim of this work is to find some methodologies for object detection and distance estimation that can be applied to unmanned aircraft vehicles. To tackle this problem, stereo vision theory and the most important object detection algorithms are studied, finding for each the best qualities. Object detection algorithms are merged with stereo vision system to find two new algorithms that want to improve the performances of the simple vision system. These two algorithms are also tested and compared in real and simulated scenarios