Thursday, 30 May 2019
Wednesday, 19 September 2018
CVPR Spotlight talk
Published at CVPR2018.
Here we explore a new problem for egocentric perception. The study of how to determine who is better at a task in an unsupervised manner. We use Deep methods to rank videos in both medical tasks -for which there is expert scoring for validation- and also for the more complex daily living tasks -for which the scoring is ambiguous-.
Posted by Walterio Mayol at 19:06
Saturday, 1 September 2018
Janis Stolzenwald, Walterio W. Mayol-Cuevas. "I Can See Your Aim: Estimating User Attention From Gaze For Handheld Robot Collaboration". IROS 2018.
Also see www.handheldrobotics.org for extended information on this project line.
Posted by Walterio Mayol at 20:18
Tuesday, 1 May 2018
Where can i do this? Geometric Affordances from a Single Example with the Interaction Tensor (ICRA2018)
Eduardo Ruiz, Walterio W. Mayol-Cuevas: Where can i do this? Geometric Affordances from a Single Example with the Interaction Tensor. ICRA 2018.
This paper introduces and evaluates a new tensor field representation to express the geometric affordance of one object over another. Evaluations also include crowdsourcing comparisons that confirm the validity of our affordance proposals, which agree on average 84% of the time with human judgments, which is 20-40% better than the baseline methods.
Posted by Walterio Mayol at 20:32
Tuesday, 24 October 2017
"Visual Odometry for Pixel Processor Arrays [PDF]", Laurie Bose, Jianing Chen, Stephen J. Carey, Piotr Dudek and Walterio Mayol-Cuevas. International Conference on Computer Vision (ICCV), Venice, Italy, 2017.
ICCV2017 Spotlight Talk
We present an approach of estimating constrained egomotion on a Pixel Processor Array (PPA). These devices embed processing and data storage capability into the pixels of the image sensor, allowing for fast and low power parallel computation directly on the image plane. Rather than the standard visual pipeline whereby whole images are transferred to an external general processing unit, our approach performs all computation upon the PPA itself, with the camera’s estimated motion as the only information output. Our approach estimates 3D rotation and a 1D scale less estimate of translation. We introduce methods of image scaling, rotation and alignment which are performed solely upon the PPA itself and form the basis for conducting motion estimation. We demonstrate the algorithms on a SCAMP-5 vision chip, achieving frame rates higher than 1000Hz and at about 2W power consumption. project website www.project-agile.org
Posted by Walterio Mayol at 19:33
Friday, 20 October 2017
Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video (ICCV2017)
Trespassing the Boundaries: Labeling Temporal Bounds for Object Interactions in Egocentric Video. D Moltisanti, M Wray, W Mayol-Cuevas, D Damen. International Conference on Computer Vision (ICCV), 2017. pdf
Posted by Walterio Mayol at 19:49
Monday, 25 September 2017
"Tracking control of a UAV with a parallel visual processor", C. Greatwood, L. Bose, T. Richardson, W. Mayol-Cuevas, J. Chen, S.J. Carey and P. Dudek, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 [PDF].
This paper presents a vision-based control strategy for tracking a ground target using a novel vision sensor featuring a processor for each pixel element. This enables computer vision tasks to be carried out directly on the focal plane in a highly efficient manner rather than using a separate general purpose computer. The strategy enables a small, agile quadrotor Unmanned Air Vehicle (UAV) to track the target from close range using minimal computational effort and with low power consumption. The tracking algorithm exploits the parallel nature of the visual sensor, enabling high rate image processing ahead of any communication bottleneck with the UAV controller. With the vision chip carrying out the most intense visual information processing, it is computationally trivial to compute all of the controls for tracking onboard. This work is directed toward visual agile robots that are power efficient and that ferry only useful data around the information and control pathways.
Visit the project website at:
Posted by Walterio Mayol at 19:07
Wednesday, 8 March 2017
Automated capture and delivery of assistive task guidance with an eyewear computer: The GlaciAR system (Augmented Human 2017)
An approach that allows both automatic capture and delivery of mixed reality guidance fully onboard Google Glass.
From the paper:
Teesid Leelasawassuk, Dima Damen, Walterio Mayol-Cuevas, Automated capture and delivery of assistive task guidance with an eyewear computer: The GlaciAR system. Augmented Human 2017.
In this paper we describe and evaluate an assistive mixed reality system that aims to augment users in tasks by combining automated and unsupervised information collection with minimally invasive video guides. The result is a fully self-contained system that we call GlaciAR (Glass-enabled Contextual Interactions for Augmented Reality). It operates by extracting contextual interactions from observing users performing actions. GlaciAR is able to i) automatically determine moments of relevance based on a head motion attention model, ii) automatically produce video guidance information, iii) trigger these guides based on an object detection method, iv) learn without supervision from observing multiple users and v) operate fully on-board a current eyewear computer (Google Glass). We describe the components of GlaciAR together with user evaluations on three tasks. We see this work as a first step toward scaling up the notoriously difficult authoring problem in guidance systems and an exploration of enhancing user natural abilities via minimally invasive visual cues.
Posted by Walterio Mayol at 22:30
Wednesday, 4 November 2015
Posted by Walterio Mayol at 15:42
Building on our previous work, we demonstrate how it is possible to improve flight control of a MAV that experiences aerodynamic disturbances caused by objects on its path. Predictions based on low resolution depth images taken at a distance are incorporated into the flight control loop on the throttle channel as this is adjusted to target undisrupted level flight. We demonstrate that a statistically significant improvement (p << 0:001) is possible for some common obstacles such as boxes and steps, compared to using conventional feedback-only control. Our approach and results are encouraging toward more autonomous MAV exploration strategies.
- John Bartholomew, Andrew Calway, Walterio Mayol-Cuevas, Improving MAV Control by Predicting Aerodynamic Effects of Obstacles. IEEE/RSJ International Conference on Intelligent Robots and Systems. September 2015. [PDF]
Posted by Walterio Mayol at 15:22
- Luis Contreras Toledo, Walterio Mayol-Cuevas, Trajectory-Driven Point Cloud Compression Techniques for Visual SLAM. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). October 2015. [PDF]
Posted by Walterio Mayol at 15:20
Tuesday, 1 September 2015
How to obtain attention for an eyewear computer without a gaze tracker? We developed this method for Google Glass.
This paper concerns with the evaluation of methods for the estimation of both temporal and spatial visual attention using a head-worn inertial measurement unit (IMU). Aimed at tasks where there is a wearer-object interaction, we estimate the when and the where the wearer is interested in. We evaluate various methods on a new egocentric dataset from 8 volunteers and compare our results with those achievable with a commercial gaze tracker used as ground-truth. Our approach is primarily geared for sensor-minimal EyeWear computing.
- Teesid Leelasawassuk, Dima Damen, Walterio W Mayol-Cuevas, Estimating Visual Attention from a Head Mounted IMU. ISWC '15 Proceedings of the 2015 ACM International Symposium on Wearable Computers. ISBN 978-1-4503-3578-2, pp. 147–150. September 2015. PDF, 2045 Kbytes. External information
Posted by Walterio Mayol at 00:00
Wednesday, 6 May 2015
Two papers related to RGBD mapping from a nice collaboration with Daniel Gutierrez and Josechu Guerrero from the University of Zaragoza. Both to be presented at ICRA 2015. One of them nominated for Awards:
- D. Gutiérrez-Gómez, W. Mayol-Cuevas, J.J. Guerrero. "Inverse Depth for Accurate Photometric and Geometric Error Minimisation in RGB-D Dense Visual Odometry", In IEEE International Conference on Robotics and Automation (ICRA), 2015. Nominated for Best Robotic Vision Paper Award. [pdf][video][code available]
- D. Gutiérrez-Gómez, W. Mayol-Cuevas, J.J. Guerrero. "What Should I Landmark? Entropy of Normals in Depth Juts for Place Recognition in Changing Environments Using RGB-D Data", In IEEE International Conference on Robotics and Automation (ICRA), 2015.[pdf]
Posted by Walterio Mayol at 23:36
Monday, 1 September 2014
We have been working for 2.5 years on prototypes (and since 2006 in the concept!) on what we think is a new extended type of robot. Handheld robots have the shape of tools and are intended to have cognition and action while cooperating with people. This video is from our first prototype back in November 2013. We are also offering details of its construction and 3D CAD models at www.handheldrobotics.org . We are currently developing a new prototype and more on this soon. Austin Gregg-Smith is sponsored by the James Dyson Foundation.
- Austin Gregg-Smith and Walterio Mayol. The Design and Evaluation of a Cooperative Handheld Robot. IEEE International Conference on Robotics and Automation (ICRA). Seattle, Washington, USA. May 25th-30th, 2015. [PDF] Nominated for Best Cognitive Robotics Paper Award.
Posted by Walterio Mayol at 18:34
Saturday, 9 August 2014
Dealing with real transparent objects for AR is challenging due to their lack of texture and visual features as well as the drastic changes in appearance as the background, illumination and camera pose change. In this work, we explore the use of a learning approach for classifying transparent objects from multiple images with the aim of both discovering such objects and building a 3D reconstruction to support convincing augmentations. We extract, classify and group small image patches using a fast graph-based segmentation and employ a probabilistic formulation for aggregating spatially consistent glass regions. We demonstrate our approach via analysis of the performance of glass region detection and example 3D reconstructions that allow virtual objects to interact with them.
From our paper: Alan Francisco Torres-Gomez, Walterio Mayol-Cuevas, Recognition and reconstruction of transparent objects for Augmented Reality. ISMAR 2014. PDF available at here.
Posted by Walterio Mayol at 16:30
Friday, 1 August 2014
Discovering Task Relevant Objects, their Usage and Providing Video Guides from Multi-User Egocentric Video
- Damen, Dima and Leelasawassuk, Teesid and Haines, Osian and Calway, Andrew and Mayol-Cuevas, Walterio (2014). You-Do, I-Learn: Discovering Task Relevant Objects and their Modes of Interaction from Multi-User Egocentric Video. British Machine Vision Conference (BMVC), Nottingham, UK. [pdf]
- Damen, Dima and Haines, Osian and Leelasawassuk, Teesid and Calway, Andrew and Mayol-Cuevas, Walterio (2014). Multi-user egocentric Online System for Unsupervised Assistance on Object Usage. ECCV Workshop on Assistive Computer Vision and Robotics (ACVR), Zurich, Switzerland. [preprint]
Posted by Walterio Mayol at 17:36
Wednesday, 23 April 2014
With the current "easiness" with which 3D maps are now possible to be constructed, this work in a way aims to enhance maps with information that is beyond purely geometric. We have also closed the control loop so we correct for the deviation in anticipation, but that is for another paper.
- John Bartholomew, Andrew Calway and Walterio Mayol-Cuevas, Learning to Predict Obstacle Aerodynamics from Depth Images for Micro Air Vehicles by , IEEE ICRA 2014. [PDF]
Posted by Walterio Mayol at 23:31
Saturday, 12 October 2013
How to get a 3D model of something one looks at without any clicks or even feedback to the user?
From our paper T. Leelasawassuk and W.W. Mayol-Cuevas. 3D from Looking: Using Wearable Gaze Tracking for Hands-Free and Feedback-Free Object Modelling. ISWC 2013.
Posted by Walterio Mayol at 19:23
Monday, 1 July 2013
Image from our Advanced Robotics Journal paper
Real-time 3D simultaneous localization and map-building for a dynamic walking humanoid robot
S Yoon, S Hyung, M Lee, KS Roh, SH Ahn, A Gee, P Bunnun, A Calway, & WW Mayol-Cuevas,
Advanced Robotics, published online on May 1st, 2013.
Posted by Walterio Mayol at 01:00
Friday, 28 June 2013
In this work we present our fast (50Hz) relocalisation method based on simple visual descriptors plus a 3D geometrical test for a system performing visual 6-D relocalisation at every single frame and in real time. Continuous relocalisation is useful in re-exploration of scenes or for loop-closure in earnest. Our experiments suggest the feasibility of this novel approach that benefits from depth camera data, with a relocalisation performance of 73% while running on a single core onboard a moving platform over trajectory segments of about 120m. The system also reduces in 95% the memory footprint compared to a system using conventional SIFT-like descriptors.
- J. Martinez-Carranza, Walterio Mayol-Cuevas. Real-Time Continuous 6D Relocalisation for Depth Cameras. Workshop on Multi VIew Geometry in RObotics (MVIGRO), in conjunction with Robotics Science and Systems RSS. Berlin, Germany. June, 2013. PDF
- J. Martinez Carranza, A. Calway, W. Mayol-Cuevas, Enhancing 6D visual relocalisation with depth cameras. International Conference on Intelligent Robots and Systems IROS. November 2013.
Posted by Walterio Mayol at 18:47
Wednesday, 1 May 2013
These videos show work we been doing with our partners at Blue Bear for onboard visual mapping for MAVs. These are based on visual odometry mapping for working over large areas and build maps onboard the MAV using an asus xtion-pro RGBD camera mounted on the vehicle. One of the videos show autoretrieval of the vehicle where a human pilot first flies the vehicle through the space and then the map is used for relocalisation using the map built on the way back. The other video is on a nuclear reactor installation. These are works we been doing for a while on uses of our methods for industrial inspection.
Posted by Walterio Mayol at 23:14
Monday, 25 March 2013
March 2013 New Robotics MSc. I redesigned our joint MSc in Robotics which is now aimed to support students from various backgrounds in Engineering, Physics and Maths. I am looking forward to supervise MSc project here. Have a look at the programme here. The application deadline is August 31st.
Posted by Walterio Mayol at 03:27
Thursday, 1 November 2012
Click image for video
- Pished Bunnun, Dima Damen, Andrew Calway, Walterio Mayol-Cuevas, Integrating 3D Object Detection, Modelling and Tracking on a Mobile Phone. International Symposium on Mixed and Augmented Reality (ISMAR). November 2012. PDF.
Posted by Walterio Mayol at 14:56
Sunday, 7 October 2012
How does a UAV can decide where is best to land and what to expect if landing on a particular material? Here we develop a framework to predict the landing behaviour of a Micro Air Vehicle (MAV) from the visual appearance of the landing surface. We approach this problem by learning a mapping from visual texture observed from an onboard camera to the landing behaviour on a set of sample materials. In this case we exemplify our framework by predicting the yaw angle of the MAV after landing.
- John Bartholomew, Andrew Calway, Walterio Mayol-Cuevas, Predicting Micro Air Vehicle Landing Behaviour from Visual Texture . IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). October 2012. PDF.
Posted by Walterio Mayol at 16:45
We developed an integrated system for personal workspace monitoring based around an RGB-D sensor. The approach is egocentric, facilitating full flexibility, and operates in real-time, providing object detection and recognition, and 3D trajectory estimation whilst the user undertakes tasks in the workspace. A prototype on-body system developed in the context of work-flow analysis for industrial manipulation and assembly tasks is described. We evaluated on two tasks with multiple users, and results indicate that the method is effective, giving good accuracy performance.
Posted by Walterio Mayol at 16:00
Monday, 3 September 2012
Relocalisation is about finding out where the camera is in translation and rotation (6D) when it visits the space for the first time after a map has been created, or if gets lost during tracking due to occlusion. This is also known as the "kidnapped robot" problem in Robotics and appears frequently in SLAM at the loopclosing stage. Here, we develop a fast relocalisation method for RGB-D cameras that operates in workplaces where low texture and some occlusion can be present. Videos are available here.
- Andrew P. Gee, Walterio Mayol-Cuevas, 6D Relocalisation for RGBD Cameras Using Synthetic View Regression. Proceedings of the British Machine Vision Conference (BMVC). September 2012. PDF.
Posted by Walterio Mayol at 19:13