Estimacion de carga muscular mediante imagenes

Classés selon la proximité de leur titre et de leur résumé avec ceux de cet article. Sélectionnez-en pour les lire ensemble.

Les articles les plus proches

1. Apparenté Pas pertinent

   Image-based Stability Quantification

   Jesse Scott, John Challis, Robert T. Collins et al. · 2022 · Vision par ordinateur et reconnaissance de formes · Résumé IA disponible

   Résumé scientifique

   Quantitative evaluation of human stability using foot pressure/force measurement hardware and motion capture (mocap) technology is expensive, time consuming, and restricted to the laboratory. We propose a novel image-based method to estimate three key components for stability computation: Center of Mass (CoM), Base of Support (BoS), and Center of Pressure (CoP). Furthermore, we quantitatively validate our image-based methods for computing two classic stability measures, CoMtoCoP and CoMtoBoS distances, against values generated directly from laboratory-based sensor output (ground truth) using a publicly available, multi-modality (mocap, foot pressure, two-view videos), ten-subject human motio…

2. Apparenté Pas pertinent

   Real-time Recognition of Yoga Poses using computer Vision for Smart Health Care

   Abhishek Sharma, Yash Shah, Yash Agrawal et al. · 2022 · Vision par ordinateur et reconnaissance de formes · Pas encore résumé

   Résumé scientifique

   Nowadays, yoga has become a part of life for many people. Exercises and sports technological assistance is implemented in yoga pose identification. In this work, a self-assistance based yoga posture identification technique is developed, which helps users to perform Yoga with the correction feature in Real-time. The work also presents Yoga-hand mudra (hand gestures) identification. The YOGI dataset has been developed which include 10 Yoga postures with around 400-900 images of each pose and also contain 5 mudras for identification of mudras postures. It contains around 500 images of each mudra. The feature has been extracted by making a skeleton on the body for yoga poses and hand for mudra …

3. Apparenté Pas pertinent

   QUIZ: An Arbitrary Volumetric Point Matching Method for Medical Image Registration

   Lin Liu, Xinxin Fan, Haoyang Liu et al. · 2023 · Vision par ordinateur et reconnaissance de formes · Pas encore résumé

   Résumé scientifique

   Rigid pre-registration involving local-global matching or other large deformation scenarios is crucial. Current popular methods rely on unsupervised learning based on grayscale similarity, but under circumstances where different poses lead to varying tissue structures, or where image quality is poor, these methods tend to exhibit instability and inaccuracies. In this study, we propose a novel method for medical image registration based on arbitrary voxel point of interest matching, called query point quizzer (QUIZ). QUIZ focuses on the correspondence between local-global matching points, specifically employing CNN for feature extraction and utilizing the Transformer architecture for global p…

4. Apparenté Pas pertinent

   Learnable human mesh triangulation for 3D human pose and shape estimation

   Sungho Chun, Sungbum Park, Ju Yong Chang · 2022 · Vision par ordinateur et reconnaissance de formes · Pas encore résumé

   Résumé scientifique

   Compared to joint position, the accuracy of joint rotation and shape estimation has received relatively little attention in the skinned multi-person linear model (SMPL)-based human mesh reconstruction from multi-view images. The work in this field is broadly classified into two categories. The first approach performs joint estimation and then produces SMPL parameters by fitting SMPL to resultant joints. The second approach regresses SMPL parameters directly from the input images through a convolutional neural network (CNN)-based model. However, these approaches suffer from the lack of information for resolving the ambiguity of joint rotation and shape reconstruction and the difficulty of net…

5. Apparenté Pas pertinent

   Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations

   Thomas Yerxa, Yilun Kuang, Eero Simoncelli et al. · 2023 · Vision par ordinateur et reconnaissance de formes · Résumé IA disponible

   Résumé scientifique

   The efficient coding hypothesis proposes that the response properties of sensory systems are adapted to the statistics of their inputs such that they capture maximal information about the environment, subject to biological constraints. While elegant, information theoretic properties are notoriously difficult to measure in practical settings or to employ as objective functions in optimization. This difficulty has necessitated that computational models designed to test the hypothesis employ several different information metrics ranging from approximations and lower bounds to proxy measures like reconstruction error. Recent theoretical advances have characterized a novel and ecologically releva…

6. Apparenté Pas pertinent

   Matlab Implementation of Machine Vision Algorithm on Ballast Degradation Evaluation

   Zixu Zhao · 2018 · Vision par ordinateur et reconnaissance de formes · Pas encore résumé

   Résumé scientifique

   America has a massive railway system. As of 2006, U.S. freight railroads have 140,490 route- miles of standard gauge, but maintaining such a huge system and eliminating any dangers, like reduced track stability and poor drainage, caused by railway ballast degradation require huge amount of labor. The traditional way to quantify the degradation of ballast is to use an index called Fouling Index (FI) through ballast sampling and sieve analysis. However, determining the FI values in lab is very time-consuming and laborious, but with the help of recent development in the field of computer vision, a novel method for a potential machine-vison based ballast inspection system can be employed that ca…

7. Apparenté Pas pertinent

   Forensic Scanner Identification Using Machine Learning

   Ruiting Shao, Edward J. Delp · 2020 · Vision par ordinateur et reconnaissance de formes · Résumé IA disponible

   Résumé scientifique

   Due to the increasing availability and functionality of image editing tools, many forensic techniques such as digital image authentication, source identification and tamper detection are important for forensic image analysis. In this paper, we describe a machine learning based system to address the forensic analysis of scanner devices. The proposed system uses deep-learning to automatically learn the intrinsic features from various scanned images. Our experimental results show that high accuracy can be achieved for source scanner identification. The proposed system can also generate a reliability map that indicates the manipulated regions in an scanned image.

8. Apparenté Pas pertinent

   LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images

   Gregory Rogez, Philippe Weinzaepfel, Cordelia Schmid · 2018 · Vision par ordinateur et reconnaissance de formes · Résumé IA disponible

   Résumé scientifique

   We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals per image, which allows us to predict 2D and 3D poses of multiple people simultaneously. Hence, our approach does not require an approximate localization of the humans for initialization. Our Localization-Classification-Regression architecture, named LCR-Net, contains 3 main components: 1) the pose proposal generator that suggests candidate poses at different locations in the image; 2) a classifier that scores the different pose proposals; and 3) a regressor that refines pose proposals both in 2D and 3D. All three s…