کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4969266 1449928 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Collaborative sparse representation leaning model for RGBD action recognition
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Collaborative sparse representation leaning model for RGBD action recognition
چکیده انگلیسی
Multi-modalities action recognition becomes a hot research topic, and this paper proposes a collaborative sparse representation leaning model for RGB-D action recognition where RGB and depth information are adaptive fused. Specifically, dense trajectory feature is firstly extracted and Bag-of-Word (BoW) weight scheme is employed for RGB modality, and then for depth modality, the human pose representation model (HPM) and temporal modeling (TM) representation are utilized. Meanwhile, the collaborative reconstruction structure and corresponding objective functions for the multiple modalities are designed, and then the proposed model is collaboratively optimized which is used to discover the latent complementary information between RGB and depth data. Finally, the collaborative reconstruction error is employed as our classification scheme. Large scale experimental results on challenging and public DHA, M2I and Northwestern-UCLA action datasets show that the performances of our model on two modalities are much better than traditional sole modality, which can boost the performance of human action recognition by taking advance of complementary characteristics from both RGB and depth modalities.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Visual Communication and Image Representation - Volume 48, October 2017, Pages 442-452
نویسندگان
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