کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4948625 1439619 2016 27 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Local Surface Geometric Feature for 3D human action recognition
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Local Surface Geometric Feature for 3D human action recognition
چکیده انگلیسی
This paper presents a novel Local Surface Geometric Feature (LSGF) for human action recognition from video sequences captured by a depth camera. The LSGF is extracted from each skeleton joint in point cloud space to capture the static appearance and pose cues, which includes joint position, normal, and local curvature. A temporal pyramid of covariance matrix is exploited to model both pairwise relations of features instead of features themselves and the temporal evolution. Finally, Fisher vector encoding is imported as a global representation for a video sequence and SVM classifier is used for classification. In the extensive experiments, we achieve classification results superior to most of previous published results on three public benchmark datasets, i.e., MSR-Action3D, MSR DailyActivity3D, and UTKinect Action.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 208, 5 October 2016, Pages 281-289
نویسندگان
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