Computer Vision and Pattern Recognition Technologies for Construction

This book will be of particular interest to academics, researchers, and graduate students at universities and industrial practitioners seeking to apply mobile and pervasive computing systems to improve construction industry productivity.

A Novel Geometric Algorithm for Blind Image Restoration Based on High-Dimensional Space

A novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications.

Computer vision tools for low-cost and noninvasive measurement of autism-related behaviors in infants.

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated which promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests that behavioral signs can be observed late in the first year of life. Many of these studies involve extensive frame-by-frame video observation and analysis of a child's natural behavior. Although nonintrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are burdensome for clinical and large population research purposes. This work is a first milestone in a long-term project on non-invasive early observation of children in order to aid in risk detection and research of neurodevelopmental disorders. We focus on providing low-cost computer vision tools to measure and identify ASD behavioral signs based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure responses to general ASD risk assessment tasks and activities outlined by the AOSI which assess visual attention by tracking facial features. We show results, including comparisons with expert and nonexpert clinicians, which demonstrate that the proposed computer vision tools can capture critical behavioral observations and potentially augment the clinician's behavioral observations obtained from real in-clinic assessments.

Computer vision tools for the non-invasive assessment of autism-related behavioral markers

The early detection of developmental disorders is key to child outcome, allowing interventions to be initiated that promote development and improve prognosis. Research on autism spectrum disorder (ASD) suggests behavioral markers can be observed late in the first year of life. Many of these studies involved extensive frame-by-frame video observation and analysis of a child's natural behavior. Although non-intrusive, these methods are extremely time-intensive and require a high level of observer training; thus, they are impractical for clinical and large population research purposes. Diagnostic measures for ASD are available for infants but are only accurate when used by specialists experienced in early diagnosis. This work is a first milestone in a long-term multidisciplinary project that aims at helping clinicians and general practitioners accomplish this early detection/measurement task automatically. We focus on providing computer vision tools to measure and identify ASD behavioral markers based on components of the Autism Observation Scale for Infants (AOSI). In particular, we develop algorithms to measure three critical AOSI activities that assess visual attention. We augment these AOSI activities with an additional test that analyzes asymmetrical patterns in unsupported gait. The first set of algorithms involves assessing head motion by tracking facial features, while the gait analysis relies on joint foreground segmentation and 2D body pose estimation in video. We show results that provide insightful knowledge to augment the clinician's behavioral observations obtained from real in-clinic assessments.

Facial and expression recognition for the blind using computer vision

Gemstone Team FACE

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Impact of geometric variations on delivered dose in highly focused single vocal cord IMRT

Purpose. To investigate the robustness of single vocal cord intensity modulated radiation therapy (IMRT) treatment plans for set-up errors, respiration, and deformation. Material and methods. Four-dimensional computed tomography (4D-CT) scans of 10 early glottic carcinoma patients, previously treated with conventional techniques, were used in this simulation study. For each patient a pre-treatment 4D-CT was used for IMRT planning, generating a reference dose distribution. Prescribed PTV dose was 66 Gy. The impact of systematic set-up errors was simulated by applying shifts of ± 2 mm to the planning CT scans, followed by dose re-calculation with original beam segments, MUs, etc. Effects of respiration and deformation were determined utilizing extreme inhale and exhale CT scans, and repeat scans acquired after 22 Gy, 44 Gy, and 66 Gy, respectively. All doses were calculated using Monte Carlo dose simulations. Results. Considering all investigated geometrical perturbations, reductions in the clinical target volume (CTV) V95%, D98%, D2%, and generalized equivalent uniform dose (gEUD) were limited to 1.2 ± 2.2%, 2.4 ± 2.9%, 0.2 ± 1.8%, and 0.6 ± 1.1 Gy, respectively. The near minimum dose, D98%, was always higher than 89%, and gEUD always remained higher than 66 Gy. Planned contra-lateral (CL) vocal cord DMean, gEUD, and V40 Gy were 38.2 ± 6.0 Gy, 43.4 ± 5.6 Gy, and 42.7 ± 14.9%. With perturbations these values changed by -0.1 ± 4.3 Gy, 0.1 ± 4.0 Gy, and -1.0 ± 9.6%, respectively. Conclusions. On average, CTV dose reductions due to geometrical perturbations were very low, and sparing of the CL vocal cord was maintained. In a few observations (6 of 103 simulated situations), the near-minimum CTV-dose was around 90%, requiring attention in deciding on a future clinical protocol. 

Integrated multi-scale architecture of the cortex with application to computer vision

Tese de dout., Engenharia Electrónica e de Computadores, Faculdade de Ciência e Tecnologia, Universidade do Algarve, 2007

A computer vision based web application for tracking soccer players

Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport's world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game. © 2014 Springer International Publishing.