Concept

Pose (computer vision)

Publications associées (129)

Precise Hand Finger Width Estimation via RGB-D Data

We propose a novel application of pose estimation to precisely measure the hand ﬁnger width via noisy RGB-D image. A framework is developed that estimates the ﬁnger width given data from TrueDepth camera as well as the target ﬁnger measure- ment location. ...

2020

Real-time, low-latency closed-loop feedback using markerless posture tracking

Alexander Mathis, Mackenzie Mathis

The ability to control a behavioral task or stimulate neural activity based on animal behavior in real-time is an important tool for experimental neuroscientists. Ideally, such tools are (1) noninvasive, (2) low-latency, and (3) provide interfaces to trigg ...

Neuroscience2020

Real-time, low-latency closed-loop feedback using markerless posture tracking

Alexander Mathis, Mackenzie Mathis

The ability to control a behavioral task or stimulate neural activity based on animal behavior in real-time is an important tool for experimental neuroscientists. Ideally, such tools are noninvasive, low-latency, and provide interfaces to trigger external ...

2020

Neural Scene Decomposition for Multi-Person Motion Capture

Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin

Learning general image representations has proven key to the success of many computer vision tasks. For example, many approaches to image understanding problems rely on deep networks that were initially trained on ImageNet, mostly because the learned featu ...

IEEE2019

Inferring Assembly Objects and Sequences from Demonstrations

Mahdi Nobar

Various unsupervised learning algorithms including GMM, Birch, Mean- Shift, K-means and DBSCAN were used to cluster the image and depth sensor data. However, it was not possible to ﬁt the clusters on each objects quite separately in as much as data are too ...

2019

Robot Identification and Localization with Pointing Gestures

We propose a novel approach to establish the relative pose of a mobile robot with respect to an operator that wants to interact with it; we focus on scenarios in which the robot is in the same environment as the operator, and is visible to them. The approa ...

2019

Learning an event sequence embedding for event-based deep stereo

François Fleuret, Stepan Tulyakov, Michael Hirsch

Today, a frame-based camera is the sensor of choice for machine vision applications. However, these cameras, originally developed for acquisition of static images rather than for sensing of dynamic uncontrolled visual environments, suffer from high power c ...

IEEE2019

Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI settings. Accurate methods have been proposed recently, but they usually rely o ...

2019

SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion

Jean-Philippe Thiran, Mohammad Saeed Rad

Despite well-established baselines, learning of scene depth and ego-motion from monocular video remains an ongoing challenge, specifically when handling scaling ambiguity issues and depth inconsistencies in image sequences. Much prior work uses either a su ...

IEEE COMPUTER SOC2019

Pretraining boosts out-of-domain robustness for pose estimation

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Mert Yüksekgönül

Deep neural networks are highly effective tools for human and animal pose estimation. However, robustness to out-of-domain data remains a challenge. Here, we probe the transfer and generalization ability for pose estimation with two architecture classes (M ...

2019

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