GaitRef: Gait Recognition with Refined Sequential Skeletons

Identifying humans with their walking sequences, known as gait recognition, is a useful biometric understanding task as it can be observed from a long distance and does not require cooperation from the subject. Two common modalities used for representing the walking sequence of a person are silhouettes and joint skeletons. Silhouette sequences, which record the boundary of the walking person in each frame, may suffer from the variant appearances from carried-on objects and clothes of the person. Framewise joint detections are noisy and introduce some jitters that are not consistent with sequential detections. In this paper, we combine the silhouettes and skeletons and refine the framewise joint predictions for gait recognition. With temporal information from the silhouette sequences. We show that the refined skeletons can improve gait recognition performance without extra annotations. We compare our methods on four public datasets, CASIA-B, OUMVLP, Gait3D and GREW, and show state-of-the-art performance.Comment: IJCB 2023. Code is available at https://github.com/haidongz-usc/GaitRe

ShARc: Shape and Appearance Recognition for Person Identification In-the-wild

Identifying individuals in unconstrained video settings is a valuable yet challenging task in biometric analysis due to variations in appearances, environments, degradations, and occlusions. In this paper, we present ShARc, a multimodal approach for video-based person identification in uncontrolled environments that emphasizes 3-D body shape, pose, and appearance. We introduce two encoders: a Pose and Shape Encoder (PSE) and an Aggregated Appearance Encoder (AAE). PSE encodes the body shape via binarized silhouettes, skeleton motions, and 3-D body shape, while AAE provides two levels of temporal appearance feature aggregation: attention-based feature aggregation and averaging aggregation. For attention-based feature aggregation, we employ spatial and temporal attention to focus on key areas for person distinction. For averaging aggregation, we introduce a novel flattening layer after averaging to extract more distinguishable information and reduce overfitting of attention. We utilize centroid feature averaging for gallery registration. We demonstrate significant improvements over existing state-of-the-art methods on public datasets, including CCVID, MEVID, and BRIAR.Comment: WACV 202

Research Progress of Computer in Medicine

With the rapid development of electronic computers, computer technology has been applied into various fields of medicine and its management. The application of computers in medical treatment has also greatly promoted the development of medical treatment. Research on the application condition of computers in medicine is of great importance to future medical care

On the Development and Present Situation of Medical Education in China

Under the background of economic globalization, carrying out medical education is of great significance for improving the level of medical education of the country. The development of medical education in China has entered a new stage of development. How to realize the integration of medical education with international standards is a question that is worth thinking. Of course, it is a long process to realize the internationalization of medical education, which requires constant persistence and improvement. While drawing on international advanced experience, we should also explore the form of medical education in China and take the international road that is most suitable for the development of medical education in China

CPARR: Category-based Proposal Analysis for Referring Relationships

The task of referring relationships is to localize subject and object entities in an image satisfying a relationship query, which is given in the form of \texttt{}. This requires simultaneous localization of the subject and object entities in a specified relationship. We introduce a simple yet effective proposal-based method for referring relationships. Different from the existing methods such as SSAS, our method can generate a high-resolution result while reducing its complexity and ambiguity. Our method is composed of two modules: a category-based proposal generation module to select the proposals related to the entities and a predicate analysis module to score the compatibility of pairs of selected proposals. We show state-of-the-art performance on the referring relationship task on two public datasets: Visual Relationship Detection and Visual Genome.Comment: CVPR 2020 Workshop on Multimodal Learnin

Clinical features and outcomes of diffuse endocapillary proliferation Henoch-Schönlein purpura nephritis in children

OBJECTIVE: To investigate the outcomes of childhood diffuse endocapillary proliferation Henoch-Schönlein purpura nephritis (DEP-HSPN) in response to early diagnosis and prompt treatment. METHODS: Eleven cases of DEP-HSPN in children were investigated in comparison to HSPN without diffuse endocapillary proliferation (non-DEP-HSPN). RESULTS: DEP-HSPN had a higher prevalence of nephrotic syndrome but a lower prevalence of hematuria compared to non-DEP-HSPN. IgA, IgG and IgM antibody deposition was found in DEP-HSPN by histopathological examination. Proteinuria cleared in all 11 cases through treatment with steroids and/or immunosuppressive drugs. However, half of the DEP-HSPN patients continuously had hematuria after treatment. CONCLUSION: The early diagnosis and prompt initiation of immunosuppressive treatment based on renal biopsy are important for achieving favorable outcomes