M
Matthew Turk
Researcher at Toyota Technological Institute at Chicago
Publications - 209
Citations - 33736
Matthew Turk is an academic researcher from Toyota Technological Institute at Chicago. The author has contributed to research in topics: Augmented reality & Facial recognition system. The author has an hindex of 55, co-authored 198 publications receiving 30972 citations. Previous affiliations of Matthew Turk include Massachusetts Institute of Technology & University of California.
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Proceedings ArticleDOI
Multi-view Appearance-based 3D Hand Pose Estimation
TL;DR: This work describes a novel approach to appearance-based hand pose estimation which relies on multiple cameras to improve accuracy and resolve ambiguities caused by selfocclusions, and forms the problem in a MAP (maximum a posteriori) framework, where the information from multiple cameras is fused to provide reliable hand poses estimation.
Proceedings ArticleDOI
Generalized autofocus
TL;DR: This work proposes a method to automatically select a minimal set of images, focused at different depths, such that all objects in a given scene are in focus in at least one image, and aims to minimize both the amount of time spent metering the scene and capturing the images, and the total amount of high-resolution data that is captured.
Proceedings ArticleDOI
What Should I Ask? Using Conversationally Informative Rewards for Goal-oriented Visual Dialog.
Pushkar Shukla,Carlos Elmadjian,Richika Sharan,Vivek Kulkarni,Matthew Turk,William Yang Wang +5 more
TL;DR: This work proposes an end-to-end goal-oriented visual dialogue system, that combines reinforcement learning with regularized information gain, and is motivated by the Rational Speech Act framework, which models the process of human inquiry to reach a goal.
Proceedings ArticleDOI
Interpreting 2D gesture annotations in 3D augmented reality
TL;DR: By first classifying which type of gesture the user drew, it is shown that it is possible to render the 2D annotations in 3D in a way that conforms more to the original intention of the user than with traditional methods.
Proceedings ArticleDOI
Discontinuity preserving stereo with small baseline multi-flash illumination
TL;DR: This paper shows how active illumination algorithms can produce a rich set of feature maps that are useful in dense 3D reconstruction and shows how they can be used in two different algorithms for dense stereo correspondence.