Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation e...Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point （STIP） based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words （BoVW） model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, which reflects salient motions and can be divided into a time salient directed graph and a space salient directed graph, aiming at adding spatio-temporal discriminant to BoVW. Generally speaking, both salient directed graphs are constructed by labeled STIPs in pairs. In detail, the ＂directional co-occurrence＂ property of different labeled pairwise STIPs in same frame is utilized to represent the time saliency, and the space saliency is reflected by the ＂geometric relationships＂ between same labeled pairwise STIPs across different frames. Then, new statistical features namely the Time Salient Pairwise feature （TSP） and the Space Salient Pairwise feature （SSP） are designed to describe two salient directed graphs, respectively. Experiments are carried out with a homogeneous kernel SVM classifier, on four challenging datasets KTH, ADL and UT-Interaction. Final results confirm the complementary of TSP and SSP, and our multi-cue representation TSP ＋ SSP ＋ BoVW can properly describe human actions with large intro-variability in real-time.展开更多
Objective: To explore the underlying molecular mechanisms of cellular response to the challenge by 1-methyl-4-phenylpyridinium (MPP+)-induced apoptosis of PC12 cells, an in vitro cell model for Parkinson’s disease, a...Objective: To explore the underlying molecular mechanisms of cellular response to the challenge by 1-methyl-4-phenylpyridinium (MPP+)-induced apoptosis of PC12 cells, an in vitro cell model for Parkinson’s disease, and the effect of NF-κB activation on the protection of Parkinson’s disease by Isoflavone (I). Methods: PC12 cells were used to establish the cell model of Parkinson’s disease, and are divided into five groups: control group;MPP+ group;I (Isoflavone) + MPP+ group;I group;SN-50 + MPP+ group. The content of NF-κB in PC12 cells was determined by immunocytochemistry;The viability of PC12 cells after treated with cell-permeable NF-κB inhibitor SN-50 and cell viability were measured by MTT assay;the expression levels of NF-κB p65 in cytoplasm and nuclear fractions were evaluated by western blot analysis;the mRNA expression of NF-κB p65 was analyzed by in situ hybridization (ISH). Results: Compared with the control group, the protein of NF-κB p65 both in cytoplasm and in nuclei was significantly higher than in I + MPP+ and MPP+ groups;similarly, the mRNA expression level of NF-κB p65 gene was also significantly higher;moreover, the protein expression of NF-κB p65 was much lower in I group (P + group, the protein of NF-κB p65 was significantly lower in I + MPP+ group, the mRNA expression level of NF-κB p65 gene was also significantly lower, and the protein expression level of NF-κB p65 was much lower in I + MPP+ group (P + group (P > 0.05). Conclusion: NF-κB activation is essential to MPP+-induced apoptosis in PC12 cells;but Isoflavone can inhibit the cell damage to some extent to execute its protective function, which may be involved in nigral neurodegeneration in patients with Parkinson’s disease.展开更多
基金This work is supported by the National Natural Science Foundation of China （NSFC, nos. 61340046）, the National High Technology Research and Development Programme of China （863 Programme, no. 2006AA04Z247）, the Scientific and Technical Innovation Commission of Shenzhen Munici-pality （nos. JCYJ20130331144631730）, and the Specialized Research Fund for the Doctoral Programme of Higher Edu- cation （SRFDP, no. 20130001110011）.
文摘Real-time Human action classification in complex scenes has applications in various domains such as visual surveillance, video retrieval and human robot interaction. While, the task is challenging due to computation efficiency, cluttered backgrounds and intro-variability among same type of actions. Spatio-temporal interest point （STIP） based methods have shown promising results to tackle human action classification in complex scenes efficiently. However, the state-of-the-art works typically utilize bag-of-visual words （BoVW） model which only focuses on the word distribution of STIPs and ignore the distinctive character of word structure. In this paper, the distribution of STIPs is organized into a salient directed graph, which reflects salient motions and can be divided into a time salient directed graph and a space salient directed graph, aiming at adding spatio-temporal discriminant to BoVW. Generally speaking, both salient directed graphs are constructed by labeled STIPs in pairs. In detail, the ＂directional co-occurrence＂ property of different labeled pairwise STIPs in same frame is utilized to represent the time saliency, and the space saliency is reflected by the ＂geometric relationships＂ between same labeled pairwise STIPs across different frames. Then, new statistical features namely the Time Salient Pairwise feature （TSP） and the Space Salient Pairwise feature （SSP） are designed to describe two salient directed graphs, respectively. Experiments are carried out with a homogeneous kernel SVM classifier, on four challenging datasets KTH, ADL and UT-Interaction. Final results confirm the complementary of TSP and SSP, and our multi-cue representation TSP ＋ SSP ＋ BoVW can properly describe human actions with large intro-variability in real-time.
文摘Objective: To explore the underlying molecular mechanisms of cellular response to the challenge by 1-methyl-4-phenylpyridinium (MPP+)-induced apoptosis of PC12 cells, an in vitro cell model for Parkinson’s disease, and the effect of NF-κB activation on the protection of Parkinson’s disease by Isoflavone (I). Methods: PC12 cells were used to establish the cell model of Parkinson’s disease, and are divided into five groups: control group;MPP+ group;I (Isoflavone) + MPP+ group;I group;SN-50 + MPP+ group. The content of NF-κB in PC12 cells was determined by immunocytochemistry;The viability of PC12 cells after treated with cell-permeable NF-κB inhibitor SN-50 and cell viability were measured by MTT assay;the expression levels of NF-κB p65 in cytoplasm and nuclear fractions were evaluated by western blot analysis;the mRNA expression of NF-κB p65 was analyzed by in situ hybridization (ISH). Results: Compared with the control group, the protein of NF-κB p65 both in cytoplasm and in nuclei was significantly higher than in I + MPP+ and MPP+ groups;similarly, the mRNA expression level of NF-κB p65 gene was also significantly higher;moreover, the protein expression of NF-κB p65 was much lower in I group (P + group, the protein of NF-κB p65 was significantly lower in I + MPP+ group, the mRNA expression level of NF-κB p65 gene was also significantly lower, and the protein expression level of NF-κB p65 was much lower in I + MPP+ group (P + group (P > 0.05). Conclusion: NF-κB activation is essential to MPP+-induced apoptosis in PC12 cells;but Isoflavone can inhibit the cell damage to some extent to execute its protective function, which may be involved in nigral neurodegeneration in patients with Parkinson’s disease.
