A preliminary study of micro-gestures:dataset collection and analysis with multi-modal dynamic networks

Abstract. Micro-gestures (MG) are gestures that people performed spontaneously during communication situations. A preliminary exploration of Micro-Gesture is made in this thesis. By collecting recorded sequences of body gestures in a spontaneous state during games, a MG dataset is built through Kinect V2. A novel term ‘micro-gesture’ is proposed by analyzing the properties of MG dataset. Implementations of two sets of neural network architectures are achieved for micro-gestures segmentation and recognition task, which are the DBN-HMM model and the 3DCNN-HMM model for skeleton data and RGB-D data respectively. We also explore a method for extracting neutral states used in the HMM structure by detecting the activity level of the gesture sequences. The method is simple to derive and implement, and proved to be effective. The DBN-HMM and 3DCNN-HMM architectures are evaluated on MG dataset and optimized for the properties of micro-gestures. Experimental results show that we are able to achieve micro-gesture segmentation and recognition with satisfied accuracy with these two models. The work we have done about the micro-gestures in this thesis also explores a new research path for gesture recognition. Therefore, we believe that our work could be widely used as a baseline for future research on micro-gestures

Fashion, Cooperation, and Social Interactions

Fashion plays such a crucial rule in the evolution of culture and society that it is regarded as a second nature to the human being. Also, its impact on economy is quite nontrivial. On what is fashionable, interestingly, there are two viewpoints that are both extremely widespread but almost opposite: conformists think that what is popular is fashionable, while rebels believe that being different is the essence. Fashion color is fashionable in the first sense, and Lady Gaga in the second. We investigate a model where the population consists of the afore-mentioned two groups of people that are located on social networks (a spatial cellular automata network and small-world networks). This model captures two fundamental kinds of social interactions (coordination and anti-coordination) simultaneously, and also has its own interest to game theory: it is a hybrid model of pure competition and pure cooperation. This is true because when a conformist meets a rebel, they play the zero sum matching pennies game, which is pure competition. When two conformists (rebels) meet, they play the (anti-) coordination game, which is pure cooperation. Simulation shows that simple social interactions greatly promote cooperation: in most cases people can reach an extraordinarily high level of cooperation, through a selfish, myopic, naive, and local interacting dynamic (the best response dynamic). We find that degree of synchronization also plays a critical role, but mostly on the negative side. Four indices, namely cooperation degree, average satisfaction degree, equilibrium ratio and complete ratio, are defined and applied to measure people's cooperation levels from various angles. Phase transition, as well as emergence of many interesting geographic patterns in the cellular automata network, is also observed.Comment: 21 pages, 12 figure

Slit2–Robo4 signalling promotes vascular stability by blocking Arf6 activity

Slit–Roundabout (Robo) signalling has a well-understood role in axon guidance1–5. Unlike in the nervous system, however, Slitdependent activation of an endothelial-specific Robo, Robo4, does not initiate a guidance program. Instead, Robo4 maintains the barrier function of the mature vascular network by inhibiting neovascular tuft formation and endothelial hyperpermeability induced by pro-angiogenic factors 6. In this study, we used cell biological and biochemical techniques to elucidate the molecular mechanism underlying the maintenance of vascular stability by Robo4. Here, we demonstrate that Robo4 mediates Slit2-dependent suppression of cellular protrusive activity through direct interaction with the intracellular adaptor protein paxillin and its paralogue, Hic-5. Formation of a Robo4–paxillin complex at the cell surface blocks activation of the small GTPase Arf6 and, consequently, Rac by recruitment of Arf-GAPs (ADP-ribosylation factor- directed GTPase-activating proteins) such as GIT1. Consistent with these in vitro studies, inhibition of Arf6 activity in vivo phenocopies Robo4 activation by reducing pathologic angiogenesis in choroidal and retinal vascular disease and VEGF-165 (vascular endothelial growth factor-165)-induced retinal hyperpermeability. These data reveal that a Slit2–Robo4–paxillin–GIT1 network inhibits the cellular protrusive activity underlying neovascularization and vascular leak, and identify a new therapeutic target for ameliorating diseases involving the vascular system