Human Pose Estimation from Ambiguous Pressure Recordings with Spatio-temporal Masked Transformers

Despite the impressive performance of vision-based pose estimators, they generally fail to perform well under adverse vision conditions and often don't satisfy the privacy demands of customers. As a result, researchers have begun to study tactile sensing systems as an alternative. However, these systems suffer from noisy and ambiguous recordings. To tackle this problem, we propose a novel solution for pose estimation from ambiguous pressure data. Our method comprises a spatio-temporal vision transformer with an encoder-decoder architecture. Detailed experiments on two popular public datasets reveal that our model outperforms existing solutions in the area. Moreover, we observe that increasing the number of temporal crops in the early stages of the network positively impacts the performance while pre-training the network in a self-supervised setting using a masked auto-encoder approach also further improves the results

Estimating Pose from Pressure Data for Smart Beds with Deep Image-based Pose Estimators

In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes. In this paper, we explore different strategies for detecting body pose from highly ambiguous pressure data, with the aid of pre-existing pose estimators. We examine the performance of pre-trained pose estimators by using them either directly or by re-training them on two pressure datasets. We also explore other strategies utilizing a learnable pre-processing domain adaptation step, which transforms the vague pressure maps to a representation closer to the expected input space of common purpose pose estimation modules. Accordingly, we used a fully convolutional network with multiple scales to provide the pose-specific characteristics of the pressure maps to the pre-trained pose estimation module. Our complete analysis of different approaches shows that the combination of learnable pre-processing module along with re-training pre-existing image-based pose estimators on the pressure data is able to overcome issues such as highly vague pressure points to achieve very high pose estimation accuracy.Comment: The version of record of this article, first published in Applied Intelligence, is available online at Publisher's website https://doi.org/10.1007/s10489-021-02418-y. arXiv admin note: substantial text overlap with arXiv:1908.0891

Visual Psychophysics and Physiological Optics Effect of Age and Glaucoma on the Detection of Darks and Lights

PURPOSE. We have shown previously that normal observers detect dark targets faster and more accurately than light targets, when presented in noisy backgrounds. We investigated how these differences in detection time and accuracy are affected by age and ganglion cell pathology associated with glaucoma. METHODS. We asked 21 glaucoma patients, 21 age-similar controls, and 5 young control observers to report as fast as possible the number of 1 to 3 light or dark targets. The targets were positioned at random in a binary noise background, within the central 308 of the visual field. RESULTS. We replicate previous findings that darks are detected faster and more accurately than lights. We extend these findings by demonstrating that differences in detection of darks and lights are found reliably across different ages and in observers with glaucoma. We show that differences in detection time increase at a rate of approximately 55 msec/dB at early stages of glaucoma and then remain constant at later stages at approximately 800 msec. In normal subjects, differences in detection time increase with age at a rate of approximately 8 msec/y. We also demonstrate that the accuracy to detect lights and darks is significantly correlated with the severity of glaucoma and that the mean detection time is significantly longer for subjects with glaucoma than age-similar controls. CONCLUSIONS. We conclude that differences in detection of darks and lights can be demonstrated over a wide range of ages, and asymmetries in dark/light detection increase with age and early stages of glaucoma. Keywords: retina, thalamo-cortical, light-dark, perimetry, psychophysics V isual information travels from the eye to the rest of the brain through two major pathways that signal light increments (ON) and decrements (OFF) in local regions of visual space. In mammals, ON and OFF channels remain segregated in the thalamus and combine for the first time in visual cortex. However, ON-OFF cortical mixing is incomplete and unbalanced. Although single cortical neurons receive input from both channels, ON and OFF thalamic afferents segregate in different cortical domains 1-4 and cortical current sinks generated by OFF thalamic afferents are stronger and occupy larger territory than those generated by ON afferents. Moreover, cortical responses to dark stimuli are stronger, faster, more linearly related to luminance contrast, and have better spatial and temporal resolution than responses to light stimuli. 27-30 To investigate if dark/light asymmetries are affected by glaucoma within the central 308 of fixation, we asked human observers to report the number of dark or light targets presented in binary noise on a monitor screen. Our results demonstrated that darks are detected more accurately and faster than lights in control observers and observers with glaucoma. Moreover, we showed that these dark/light asymmetries increase with age and in the early stages of glaucoma. METHODS We recruited 21 patients with open angle glaucoma (48-83 years old; mean, 64.7 6 7.5 years old), 21 control observers with a similar age range (49-74 years old; mean, 62.2 6 7.3 years old), and 5 young control observers (21-25 years old). The study was performed following the principles outlined in the Declaration of Helsinki. The inclusion criteria for all groups were: best corrected visual acuity of at least 0.2 logMAR units (approximately 20/30), spherical equivalent refractive error within À6 to þ2 diopters (D), cylinder correction within 3 D, clear ocular media, and absence o