Results 41 to 50 of about 11,197 (235)

Pattern discovery for object categorization [PDF]

, 2008
This paper presents a new approach for the object categorization problem. Our model is based on the successful `bag of words' approach. However, unlike the original model, image features (keypoints) are not seen as independent and orderless. Instead, our
Zhang, Edmond Yiwen, Michael Mayo, Edmond Zhang, Mayo, Michael   +3 more
core   +1 more source

FAst Detection Algorithm for 3D Keypoints (FADA-3K)

IEEE Access, 2020
3D keypoint is widely used for object recognition and pose estimation with a 3D point cloud since it has robustness against measurement noise and occlusion.
Shogo Arai, Nobuaki Fukuchi, Koichi Hashimoto   +2 more
doaj   +1 more source

FREAK: Fast Retina Keypoint [PDF]

2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012
A large number of vision applications rely on matching keypoints across images. The last decade featured an arms-race towards faster and more robust keypoints and association algorithms: Scale Invariant Feature Transform (SIFT)[17], Speed-up Robust Feature (SURF)[4], and more recently Binary Robust Invariant Scalable Keypoints (BRISK)[I6] to name a few.
Alahi, Alexandre, Ortiz, Raphaël, Vandergheynst, Pierre   +2 more
openaire   +2 more sources

A 3D Keypoints Voting Network for 6DoF Pose Estimation in Indoor Scene

Machines, 2021
This paper addresses the problem of instance-level 6DoF pose estimation from a single RGBD image in an indoor scene. Many recent works have shown that a two-stage network, which first detects the keypoints and then regresses the keypoints for 6d pose ...
Huikai Liu, Gaorui Liu, Yue Zhang, Linjian Lei, Hui Xie, Yan Li, Shengli Sun   +6 more
doaj   +1 more source

Unsupervised Learning of Category-Specific Symmetric 3D Keypoints from Point Sets [PDF]

, 2020
International audienceAutomatic discovery of category-specific 3D keypoints from a collection of objects of some category is a challenging problem. One reason is that not all objects in a category necessarily have the same semantic parts.
Demonceaux, C., Clara Fernandez-Labrador, Ajad Chhatkuli, Guerrero, Jose. J., Paudel, D.P., Demonceaux, Cédric, Jose J. Guerrero, Cédric Demonceaux, Chhatkuli, A., Gool, Luc, Van, Paudel, Danda Pani, Fernandez-Labrador, Clara, Chhatkuli, Ajad, Chhatkuli, Ajad; id_orcid, Guerrero, Jose J., Pani Paudel, Danda, Danda Pani Paudel, Paudel, Danda, Pani, Van Gool, Luc, Fernandez-Labrador, C., Gool, L.V., Luc Van Gool, Guerrero, J.J., Guerrero, Jose, J   +23 more
core   +4 more sources

DSPose: Dual-Space-Driven Keypoint Topology Modeling for Human Pose Estimation

Sensors, 2023
Human pose estimation is the basis of many downstream tasks, such as motor intervention, behavior understanding, and human–computer interaction. The existing human pose estimation methods rely too much on the similarity of keypoints at the image feature ...
Anran Zhao, Jingli Li, Hongtao Zeng, Hongren Cheng, Liangshan Dong   +4 more
doaj   +1 more source

Complex Human Pose Estimation via Keypoints Association Constraint Network

IEEE Access, 2020
Human pose estimation has attracted enormous interest in the field of human action recognition. When the human pose is complex (such as pose distortion, pose reversal, etc.) or there is background interference (multi-target, shadow, etc.), the keypoints ...
Xuan Zhu, Zhenpeng Guo, Xin Liu, Bin Li, Jinye Peng, Peirong Chen, Rongzhi Wang   +6 more
doaj   +1 more source

Comparison of 3D interest point detectors and descriptors for point cloud fusion [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2014
The extraction and description of keypoints as salient image parts has a long tradition within processing and analysis of 2D images. Nowadays, 3D data gains more and more importance.
R. Hänsch, T. Weber, O. Hellwich
doaj   +1 more source

Appearance-based keypoint clustering [PDF]

2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009
We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that belong to separate objects or background regions.
Estrada, Francisco J., Fua, Pascal, Lepetit, Vincent, Süsstrunk, Sabine   +3 more
openaire   +2 more sources

Localizing Human Keypoints beyond the Bounding Box

, 2021
Since human pose is one of the most effective and popular sources for understanding human in various applications, there have been numerous researches on detecting keypoints of human body from the image source.
Park, Soonchan, Soonchan Park, Park, Jinah, Jinah Park   +3 more
core   +1 more source