A Binocular, Foveated Active Vision System

This report documents the design and implementation of a binocular, foveated active vision system as part of the Cog project at the MIT Artificial Intelligence Laboratory. The active vision system features a three degree of freedom mechanical platform that supports four color cameras, a motion control system, and a parallel network of digital signal processors for image processing. To demonstrate the capabilities of the system, we present results from four sample visual-motor tasks.

Context-Based Vision System for Place and Object Recognition

While navigating in an environment, a vision system has to be able to recognize where it is and what the main objects in the scene are. In this paper we present a context-based vision system for place and object recognition. The goal is to identify familiar locations (e.g., office 610, conference room 941, Main Street), to categorize new environments (office, corridor, street) and to use that information to provide contextual priors for object recognition (e.g., table, chair, car, computer). We present a low-dimensional global image representation that provides relevant information for place recognition and categorization, and how such contextual information introduces strong priors that simplify object recognition. We have trained the system to recognize over 60 locations (indoors and outdoors) and to suggest the presence and locations of more than 20 different object types. The algorithm has been integrated into a mobile system that provides real-time feedback to the user.

VAMP - a vision based sensor network for health care hygiene

Adequate hand-washing has been shown to be a critical activity in preventing the transmission of infections such as MRSA in health-care environments. Hand-washing guidelines published by various health-care related institutions recommend a technique incorporating six hand-washing poses that ensure all areas of the hands are thoroughly cleaned. In this paper, an embedded wireless vision system (VAMP) capable of accurately monitoring hand-washing quality is presented. The VAMP system hardware consists of a low resolution CMOS image sensor and FPGA processor which are integrated with a microcontroller and ZigBee standard wireless transceiver to create a wireless sensor network (WSN) based vision system that can be retargeted at a variety of health care applications. The device captures and processes images locally in real-time, determines if hand-washing procedures have been correctly undertaken and then passes the resulting high-level data over a low-bandwidth wireless link. The paper outlines the hardware and software mechanisms of the VAMP system and illustrates that it offers an easy to integrate sensor solution to adequately monitor and improve hand hygiene quality. Future work to develop a miniaturized, low cost system capable of being integrated into everyday products is also discussed.

An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.

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.

A vision system for detecting paths and moving obstacles for the blind

In this paper we present a monocular vision system for a navigation aid. The system assists blind persons in following paths and sidewalks, and it alerts the user to moving obstacles which may be on collision course. Path borders and the vanishing point are de-tected by edges and an adapted Hough transform. Opti-cal flow is detected by using a hierarchical, multi-scale tree structure with annotated keypoints. The tree struc-ture also allows to segregate moving objects, indicating where on the path the objects are. Moreover, the centre of the object relative to the vanishing point indicates whether an object is approaching or not.

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

A Real Time Vision System for Autonomous Systems: Characterization during a Middle Size Match

in RoboCup 2007: Robot Soccer World Cup XI

Design, development and assessment of the Java Intelligent Tutoring System

The "Java Intelligent Tutoring System" (JITS) research project focused on designing, constructing, and determining the effectiveness of an Intelligent Tutoring System for beginner Java programming students at the postsecondary level. The participants in this research were students in the School of Applied Computing and Engineering Sciences at Sheridan College. This research involved consistently gathering input from students and instructors using JITS as it developed. The cyclic process involving designing, developing, testing, and refinement was used for the construction of JITS to ensure that it adequately meets the needs of students and instructors. The second objective in this dissertation determined the effectiveness of learning within this environment. The main findings indicate that JITS is a richly interactive ITS that engages students on Java programming problems. JITS is equipped with a sophisticated personalized feedback mechanism that models and supports each student in his/her learning style. The assessment component involved 2 main quantitative experiments to determine the effectiveness of JITS in terms of student performance. In both experiments it was determined that a statistically significant difference was achieved between the control group and the experimental group (i.e., JITS group). The main effect for Test (i.e., pre- and postiest), F( l , 35) == 119.43,p < .001, was qualified by a Test by Group interaction, F( l , 35) == 4.98,p < .05, and a Test by Time interaction, F( l , 35) == 43.82, p < .001. Similar findings were found for the second experiment; Test by Group interaction revealed F( 1 , 92) == 5.36, p < .025. In both experiments the JITS groups outperformed the corresponding control groups at posttest.