Moving Object Detection in Freely Moving Camera via Global Motion Compensation and Local Spatial Information Fusion.

Motion object detection (MOD) with freely moving cameras is a challenging task in computer vision. To extract moving objects, most studies have focused on the difference in motion features between foreground and background, which works well for dynamic scenes with relatively regular movements and variations. However, abrupt illumination changes and occlusions often occur in real-world scenes, and the camera may also pan, tilt, rotate, and jitter, etc., resulting in local irregular variations and global discontinuities in motion features. Such complex and changing scenes bring great difficulty in detecting moving objects. To solve this problem, this paper proposes a new MOD method that effectively leverages local and global visual information for foreground/background segmentation. Specifically, on the global side, to support a wider range of camera motion, the relative inter-frame transformations are optimized to absolute transformations referenced to intermediate frames in a global form after enriching the inter-frame matching pairs. The global transformation is fine-tuned using the spatial transformer network (STN). On the local side, to address the problem of dynamic background scenes, foreground object detection is optimized by utilizing the pixel differences between the current frame and the local background model, as well as the consistency of local spatial variations. Then, the spatial information is combined using optical flow segmentation methods, enhancing the precision of the object information. The experimental results show that our method achieves a detection accuracy improvement of over 1.5% compared with the state-of-the-art methods on the datasets of CDNET2014, FBMS-59, and CBD. It demonstrates significant effectiveness in challenging scenarios such as shadows, abrupt changes in illumination, camera jitter, occlusion, and moving backgrounds.

Biguanide chitosan microneedles with cell-free DNA scavenging ability for psoriasis therapy.

High levels of cell-free DNA (cfDNA) induce psoriasis. Currently, the treatment of psoriasis has the disadvantages of penetration difficulty, suppression of normal immunity, and skin irritation. In this study, biguanide chitosan microneedles (BGC-MNs) were prepared to treat psoriasis by removing cfDNA from the dermis through the skin barrier. The effects of chitosan with different bisguanidine contents on DNA-binding capacity, biocompatibility, and inflammation inhibition were compared, revealing that chitosan containing 20% bisguanidine (BGC2) was found to have the best overall performance. In vitro, BGC2 effectively cleared cfDNA and inhibited the production of inflammatory factors. BGC-MN made from BGC2 had good mechanical and solubility properties. In vivo, BGC-MNs cleared cfDNA, reduced the level of inflammatory factors in the dermis, and exerted a good therapeutic effect on mice with psoriasis. These results suggested that BGC-MNs provided a new approach to treating psoriasis in terms of scavenging cfDNA and exerting anti-inflammatory effects.