By tech | May 2, 2018 | Category Uncategorized
On April 28th our lab welcomed a number of high school students interested in joining the Lassonde School of Engineering at the Lassonde Open House. The EECS department organized lab tours where students had an opportunity to see exciting research happening here first-hand, as well as hear about undergraduate opportunities at the School. Markus Solbach, […]
Read MoreBy tech | April 6, 2018 | Category Uncategorized
We present a Polyhedral Scene Generator system which creates a random scene based on a few user parameters, renders the scene from random view points and creates a dataset containing the renderings and corresponding annotation files. We think that this generator will help to understand how a program could parse a scene if it had […]
Read MoreBy tech | April 1, 2018 | Category Uncategorized
Abstract Scene Classification has been addressed with numerous techniques in the computer vision literature. However with the increasing size of datasets in the field, it has become difficult to achieve high accuracy in the context of robotics. We overcome this problem and obtain good results through our approach. In our approach, we propose to address […]
Read MoreBy tech | March 8, 2018 | Category Uncategorized
Paper (arXiv): Totally-Looks-Like: How Humans Compare, Compared to Machines Project website. Perceptual judgment of image similarity by humans relies on a rich internal representations ranging from low-level features to high-level concepts, scene properties and even cultural associations. Exist ing methods and datasets attempting to explain perceived similarity use stimuli which arguably do not cover the […]
Read MoreBy tech | February 10, 2018 | Category Uncategorized
Abstract Indoor Localization is a primary task for social robots. We are particularly interested in how to solve this problem for a mobile robot using primarily vision sensors. This work examines a critical issue related to generalizing approaches for static environments to dynamic ones: (i) it considers how to deal with dynamic users in the […]
Read MoreBy tech | October 13, 2017 | Category Uncategorized
Vision-Based Fallen Person Detection for the Elderly Venue: ICCV 2017 Workshop: ACVR, Venice, 2017 Paper: https://arxiv.org/abs/1707.07608 Project link: https://github.com/TsotsosLab/fallen-person-detector Abstract: Falls are serious and costly for elderly people. The Centers for Disease Control and Prevention of the US reports that millions of older people, 65 and older, fall each year at least once. Serious injuries […]
Read MoreBy tech | June 2, 2017 | Category Uncategorized
Bao Chen, Raghavendar Sahdev and John Tsotsos were co-recipients of the 2017 CIPPRS/ACTIRF Best Robotics Paper at the Conference on Computer and Robot Vision (CRV). Their paper describes efforts to develop a person following robot using stereo cameras. More details about the paper are available here.
Read MoreBy tech | May 30, 2017 | Category Uncategorized
Abstract: In this paper we introduce a stereo vision based CNN tracker for a person following robot. The tracker is able to track a human in real time using an online convolutional neural network. Our approach enables the robot to follow a target under challenging situations like occlusions, appearance changes, pose changes, crouching, illumination changes […]
Read MoreBy tech | May 28, 2017 | Category Uncategorized
The Interaction of Target-Distractor Similarity and Visual Search Efficiency for Basic Features Authors: Calden Wloka, Sang-Ah Yoo, Rakesh Sengupta, and John K. Tsotsos Abstract: Visual search efficiency is commonly measured by the relationship between subject response time (RT) and display set size. Basic features are visual features for which a singleton target can be found […]
Read MoreBy tech | May 2, 2017 | Category Uncategorized
Visuospatial Functionality for Active Observers: The Same-Different Task Venue: NSERC Canadian Field Robotics Network, Ottawa, 2017 Project link: coming soon Abstract: To understand vision in computational terms brings us closer to understand how the brain works and transferring this knowledge to build machines whose visual system approaches human ability would be extremely useful in a […]
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