Human Segmentation and Tracking Survey on Masks for MADS Dataset

Human segmentation and tracking often use the outcome of person detection in the video. Thus, the results of segmentation and tracking depend heavily on human detection results in the video. With the advent of Convolutional Neural Networks (CNNs), there are excellent results in this field. Segmentation and tracking of the person in the video have significant applications in monitoring and estimating human pose in 2D images and 3D space. In this paper, we performed a survey of many studies, methods, datasets, and results for human segmentation and tracking in video. We also touch upon detecting persons as it affects the results of human segmentation and human tracking. The survey is performed in great detail up to source code paths. The MADS (Martial Arts, Dancing and Sports) dataset comprises fast and complex activities. It has been published for the task of estimating human posture. However, before determining the human pose, the person needs to be detected as a segment in the video. Moreover, in the paper, we publish a mask dataset to evaluate the segmentation and tracking of people in the video. In our MASK MADS dataset, we have prepared 28 k mask images. We also evaluated the MADS dataset for segmenting and tracking people in the video with many recently published CNNs methods.

NeuroRetriever: Automatic Neuron Segmentation for Connectome Assembly

Segmenting individual neurons from a large number of noisy raw images is the first step in building a comprehensive map of neuron-to-neuron connections for predicting information flow in the brain. Thousands of fluorescence-labeled brain neurons have been imaged. However, mapping a complete connectome remains challenging because imaged neurons are often entangled and manual segmentation of a large population of single neurons is laborious and prone to bias. In this study, we report an automatic algorithm, NeuroRetriever, for unbiased large-scale segmentation of confocal fluorescence images of single neurons in the adult Drosophila brain. NeuroRetriever uses a high-dynamic-range thresholding method to segment three-dimensional morphology of single neurons based on branch-specific structural features. Applying NeuroRetriever to automatically segment single neurons in 22,037 raw brain images, we successfully retrieved 28,125 individual neurons validated by human segmentation. Thus, automated NeuroRetriever will greatly accelerate 3D reconstruction of the single neurons for constructing the complete connectomes.

HUMAN IMAGE MATTING BASED ON CONVOLUTIONAL NEURAL NETWORK AND PRINCIPAL CURVATURES

Image matting often requires advanced image processing, especially in conditions, when small details such as hair are present in the image. In this article the hybrid method for human image matting based on convolutional neural network and principal curvatures is proposed. The U-Net based neural network is used to predict a rough foreground segmentation mask. Then the obtained foreground mask is refined by principal curvatures method to process the elongated hair-like structures. Test results show that the proposed method can improve the coarse human segmentation.

Fgf4 maintains Hes7 levels critical for normal somite segmentation clock function

During vertebrate development, the presomitic mesoderm (PSM) periodically segments into somites, which will form the segmented vertebral column and associated muscle, connective tissue, and dermis. The periodicity of somitogenesis is regulated by a segmentation clock of oscillating Notch activity. Here, we examined mouse mutants lacking only Fgf4 or Fgf8, which we previously demonstrated act redundantly to prevent PSM differentiation. Fgf8 is not required for somitogenesis, but Fgf4 mutants display a range of vertebral defects. We analyzed Fgf4 mutants by quantifying mRNAs fluorescently labeled by hybridization chain reaction within Imaris-based volumetric tissue subsets. These data indicate that FGF4 maintains Hes7 levels and normal oscillatory patterns. To support our hypothesis that FGF4 regulates somitogenesis through Hes7, we demonstrate genetic synergy between Hes7 and Fgf4, but not with Fgf8. Our data indicate that Fgf4 is potentially important in a spectrum of human Segmentation Defects of the Vertebrae caused by defective Notch oscillations.

Species-specific segmentation clock periods are due to differential biochemical reaction speeds

Although mechanisms of embryonic development are similar between mice and humans, the time scale is generally slower in humans. To investigate these interspecies differences in development, we recapitulate murine and human segmentation clocks that display 2- to 3-hour and 5- to 6-hour oscillation periods, respectively. Our interspecies genome-swapping analyses indicate that the period difference is not due to sequence differences in the HES7 locus, the core gene of the segmentation clock. Instead, we demonstrate that multiple biochemical reactions of HES7, including the degradation and expression delays, are slower in human cells than they are in mouse cells. With the measured biochemical parameters, our mathematical model accounts for the two- to threefold period difference between the species. We propose that cell-autonomous differences in biochemical reaction speeds underlie temporal differences in development between species.