Gaussian Processes with Context-Supported Priors for Active Object Localization

We devise an algorithm using a Bayesian optimization framework in conjunction with contextual visual data for the efficient localization of objects in still images. Recent research has demonstrated substantial progress in object localization and related tasks for computer vision. However, many current state-of-the-art object localization procedures still suffer from inaccuracy and inefficiency, in addition to failing to provide a principled and interpretable system amenable to high-level vision tasks. We address these issues with the current research. Our method encompasses an active search procedure that uses contextual data to generate initial bounding-box proposals for a target object. We train a convolutional neural network to approximate an offset distance from the target object. Next, we use a Gaussian Process to model this offset response signal over the search space of the target. We then employ a Bayesian active search for accurate localization of the target. In experiments, we compare our approach to a state-of-theart bounding-box regression method for a challenging pedestrian localization task. Our method exhibits a substantial improvement over this baseline regression method.Comment: 10 pages, 4 figure

Semantic Image Retrieval via Active Grounding of Visual Situations

We describe a novel architecture for semantic image retrieval---in particular, retrieval of instances of visual situations. Visual situations are concepts such as "a boxing match," "walking the dog," "a crowd waiting for a bus," or "a game of ping-pong," whose instantiations in images are linked more by their common spatial and semantic structure than by low-level visual similarity. Given a query situation description, our architecture---called Situate---learns models capturing the visual features of expected objects as well the expected spatial configuration of relationships among objects. Given a new image, Situate uses these models in an attempt to ground (i.e., to create a bounding box locating) each expected component of the situation in the image via an active search procedure. Situate uses the resulting grounding to compute a score indicating the degree to which the new image is judged to contain an instance of the situation. Such scores can be used to rank images in a collection as part of a retrieval system. In the preliminary study described here, we demonstrate the promise of this system by comparing Situate's performance with that of two baseline methods, as well as with a related semantic image-retrieval system based on "scene graphs.

Institute Brief: Supporting Individuals with Autism Spectrum Disorders: Quality Employment Practices

It has been known for decades that individuals with autism spectrum disorders (ASD), including those with significant impairment or who have behaviors that others find challenging, can work when they are given appropriate supports. It is also clear that individuals with ASD can benefit from employment. Benefits include improved emotional state, greater financial gain, decreased anxiety, greater self-esteem, and greater independence. Nonetheless, employment outcomes for individuals with ASD have traditionally been poor. Even those who do find work are often underemployed or do not hold onto jobs for a long period of time

Tools for Inclusion: Starting with Me: A Guide to Person-Centered Planning for Job Seekers

A person-centered approach can help individuals with disabilities make satisfying job choices. This brief guides job seekers through a three-stage career development process that includes assessing their interests, researching the job market, and marketing themselves to potential employers

Institute Brief: Making Experiential Education Accessible for Students with Disabilities

College students with disabilities enter with less work experience and have a harder time finding jobs than their nondisabled peers. Experiential education-- mentoring, internships, job shadowing, and so on-- can create a bridge to graduation and employment. However, that requires college professionals to consider access issues for all students. A new Institute Brief provides basic disability awareness information, suggests ways to create welcoming career offices, and offers ideas to increase access to experiential education

Starting with Me: A Guide to Person-Centered Planning for Job Seekers

[Excerpt] Work is an important part of life. People with disabilities benefit from working as much as or more than people without disabilities do. The benefits from work include financial independence and security; increased self-confidence; personal growth; skill development; and a better social life. Perhaps you would like to work but have not been encouraged to do so by your family, friends, or support people in your life. Maybe you are not certain if you can work or what kind of work might be right for you. This is a guide for you. This guide reviews a three- stage career development process. Career development is an approach to help you make satisfying job choices. In person-centered career planning, your personal preferences, goals, and dreams are the focus. A person-centered approach does not mean you have to tackle job exploration all on your own. It does mean that anyone who helps you in your career search and the development of your career dreams respects your wishes and helps you to focus on your skills and abilities. Career development is an ongoing process. Finding satisfying work doesn’t usually just happen by applying for a job in the newspaper. The process involves several phases—and it all begins with you

Tools for Inclusion: One-Stop Centers: A Guide for Job Seekers with Disabilities

General information about the One-Stop system and answers to specific questions individuals with disabilities may have about One-Stop services