Abstract. In this paper, we proposed a fast and accurate human pose estimation framework that combines top-down and bottom-up methods. The framework consists of an initialization stage and an iterative searching stage. In the initialization stage, example based method is used to find several initial poses which are used as searching seeds of the next stage. In the iterative searching stage, a larger number of body parts candidates are generated by adding random disturbance to searching seeds. Belief Propagation (BP) algorithm is applied to these candidates to find the best n poses using the information of global graph model and part image likelihood. Then these poses are further used as searching seeds for the next iteration. To model image likelihoods of parts we designed rotation invariant EdgeField features based on which we learnt boosted classifiers to calculate the image likelihoods. Experiment result shows that our framework is both fast and accurate.

Abstract. For multi-view face alignment (MVFA), the non-linear variation of shape and texture, and the self-occlusion of facial feature points caused by view change are the two major difficulties. The state-of-the-art MVFA methods are essentially view-based approaches in which views are divided into several categories such as frontal, half profile, full profile etc. and each of them has its own model in MVFA. Therefore the view estimation problem becomes a critical step in MVFA. In this paper, a MVFA method using 3D face shape model for view estimation is presented in which the 3D shape model is used to estimate the pose of the face thereby selecting its model and indicating its selfoccluded points. Experiments on different datasets are reported to show the improvement over previous works. [10] are developed which are mainly 2D approaches with no appealing to 3D face information. Due to the intrinsic difficulties caused by face appearance changes in 2D face images of a 3D face, MVFA is still not a solved problem. KeywordsThe state-of-the-art MVFA methods are essentially view-based approaches in which views are divided into several categories such as frontal, half profile, full profile etc. and each of them has its own shape and texture models. Since the texture model used in local search of each label point of a particular shape model depends on

Real-time face alignment in video is very critical in many applications such as facial expression analysis, driver fatigue monitoring, etc. This paper presents a real time algorithm for face alignment in video that combines Active Shape Model (ASM) based face alignment and spatial-temporal continuity based tracking strategy. To guarantee the correctness of the tracked shape in each frame, a verification procedure is introduced so that when inter-frame shape tracking failed the intra-frame ASM algorithm can be restored to initialize a new shape for tracking. Experiments show that the implemented system can run totally automatic with a quite good accuracy that may have many practical applications.

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Background: Postoperative delirium, a common complication after surgery in elderly individuals, is a state of acute brain dysfunction characterized by fluctuating mental status that affects millions of patients each year. We used prophylactic inhalation of hydrogen gas with elderly patients undergoing elective surgery to compare their occurrence of postoperative delirium with that of controls.Methods: A total of 184 patients were enrolled and randomized into a control group and a hydrogen inhalation group. All the patients were >= 65 years of age. The quality of sleep was assessed 1 day before surgery and 1, 3, and 7 days after surgery at 8 AM. The Confusion Assessment Method (CAM) was used as a screening tool for delirium. The patients' postoperative state of consciousness was assessed using the CAM 1-7 days after surgery. If delirium was diagnosed, the time of onset and duration of delirium were recorded.Results: Postoperative delirium happened in 17 (24%) of 70 elderly noncardiac patients and in 10 (12%) of 83 patients after hydrogen inhalation. The incidence of delirium was decreased in the hydrogen group. No significance differences were found in length of stay in the hospital after surgery between the two groups. For additional outcomes, there was no significant difference in sleep quality between the two groups at 1, 3, and 7 days postoperatively, and the sleep quality gradually recovered over 7 days postoperatively. The numerical rating scale (NRS) pain scores were higher in the hydrogen group (4.08±1.77) than in the control group (3.54±1.77) on day 1 (P<0.05); however, the mean difference in NRS pain scores between the two groups was small (1 to 1.6). There was no significant difference on day 3 or 7. The postoperative C-reactive protein level was significantly lower in the hydrogen group than in the control group.Conclusions: This study suggests that hydrogen inhalation can prevent postoperative delirium in elderly noncardiac patients by reducing the inflammatory response.