Pose-invariant features and personalized correspondence learning for face recognition
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DOI: 10.1007/s00521-017-3035-3
Abstract: In surveillance systems, face recognition plays an important role for human identification. In such systems, human faces are spatially unconstrained, which results in a significant change in pose, and face recognition becomes more challenging when… read more here.
Keywords: correspondence; pose invariant; personalized correspondence; face ... See more keywords
On the frontiers of pose invariant face recognition: a review
Sign Up to like & getrecommendations! Published in 2019 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-019-09742-3
Abstract: Computer vision systems open a new challenge to recognize human faces under varied poses in similar capacity and capability as human-beings perform naturally. For surveillance applications, pose-invariant face recognition (PIFR) will become a major break-through… read more here.
Keywords: pose invariant; review; invariant face; face recognition ... See more keywords
Pose-invariant matching for non-rigid 3D models using Isomap
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DOI: 10.1371/journal.pone.0264192
Abstract: The wide usage of 3D mesh models greatly increases the importance of an effective matching algorithm for them. In this paper, we propose a novel 3D model matching algorithm. Firstly, vertices on the input 3D… read more here.
Keywords: non rigid; rigid models; invariant matching; pose invariant ... See more keywords
Mutually reinforcing motion-pose framework for pose invariant action recognition
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DOI: 10.1504/ijbm.2019.10020082
Abstract: Action recognition from videos has many potential applications. However, there are many unresolved challenges, such as pose-invariant recognition, robustness to occlusion and others. In this paper, we propose to combine motion of body parts and… read more here.
Keywords: action recognition; pose invariant; action; mutually reinforcing ... See more keywords