arXiv subjects

Rachel Brown

Publications and source records attributed to Rachel Brown.

5 recordsLinked to original sources

arXiv2026

Computer Vision with a Superpixelation Camera

Conventional cameras generate a lot of data that can be challenging to process in resource-constrained applications. Usually, cameras generate data streams on the order of the number of pixels in the image. However, most of this captured data is redundant for many downstream computer vision algorithms. We propose a novel camera design, which we call SuperCam, that adaptively processes captured data by performing superpixel segmentation on the fly. We show that SuperCam performs better than current state-of-the-art superpixel algorithms under memory-constrained situations. We also compare how well SuperCam performs when the compressed data is used for downstream computer vision tasks. Our results demonstrate that the proposed design provides superior output for image segmentation, object detection, and monocular depth estimation in situations where the available memory on the camera is limited. We posit that superpixel segmentation will play a crucial role as more computer vision inference models are deployed in edge devices. SuperCam would allow computer vision engineers to design more efficient systems for these applications.

cs.CV↗

arXiv2024

Ekpyrosis in Quantum Gravitational Anisotropic Bouncing Models

We explore the isotropization of a model anisotropic universe in the bouncing models using the ekpyrotic potential without assuming initial conditions corresponding to an ekpyrotic phase. In particular, we explore the way the use of ekpyrotic potentials may dynamically help isotropization for the considered initial conditions corresponding to the macroscopic classical contracting universe with potentially large anisotropies. As an example of a concrete nonsingular bouncing mechanism, we consider the effective description of loop quantum cosmology for Bianchi-I and Bianchi-IX spacetimes for ekpyrotic and ekpyrotic-like potentials. Considering two different values of potential parameters and initial conditions corresponding to a classical macroscopic universe, we show that for both of these spacetimes, the cosmological singularity is resolved via multiple short-duration nonsingular bounces caused by quantum gravitational effects. We perform a large number of numerical simulations for a wide range of initial conditions which do not favor ekpyrosis initially. Even with such unfavorable initial conditions, we show that the relative strength of the anisotropies at the end of the bounce regime is noticeably reduced in more than 90% of the simulations. This provides a strong evidence for the isotropization ability of the ekpyrotic potentials. We find that isotropization can occur over cycles of rapid nonsingular bounces in the Planck regime via enhancement of the contribution of the (isotropic) energy density relative to the anisotropies at the bounces. Achieving isotropization is found to be easier in Bianchi-I spacetimes when compared to Bianchi-IX spacetimes. Our results demonstrate that, even with initial conditions which are not most favorable for the existence of ekpyrosis, an effective isotropization can occur in nonsingular anisotropic models with ekpyrotic and ekpyrotic-like potentials.

gr-qc↗

arXiv2023

The Shortest Route Is Not Always the Fastest: Probability-Modeled Stereoscopic Eye Movement Completion Time in VR

Speed and consistency of target-shifting play a crucial role in human ability to perform complex tasks. Shifting our gaze between objects of interest quickly and consistently requires changes both in depth and direction. Gaze changes in depth are driven by slow, inconsistent vergence movements which rotate the eyes in opposite directions, while changes in direction are driven by ballistic, consistent movements called saccades, which rotate the eyes in the same direction. In the natural world, most of our eye movements are a combination of both types. While scientific consensus on the nature of saccades exists, vergence and combined movements remain less understood and agreed upon. We eschew the lack of scientific consensus in favor of proposing an operationalized computational model which predicts the speed of any type of gaze movement during target-shifting in 3D. To this end, we conduct a psychophysical study in a stereo VR environment to collect more than 12,000 gaze movement trials, analyze the temporal distribution of the observed gaze movements, and fit a probabilistic model to the data. We perform a series of objective measurements and user studies to validate the model. The results demonstrate its predictive accuracy, generalization, as well as applications for optimizing visual performance by altering content placement. Lastly, we leverage the model to measure differences in human target-changing time relative to the natural world, as well as suggest scene-aware projection depth. By incorporating the complexities and randomness of human oculomotor control, we hope this research will support new behavior-aware metrics for VR/AR display design, interface layout, and gaze-contingent rendering.

cs.GR↗

arXiv2022

Image Features Influence Reaction Time: A Learned Probabilistic Perceptual Model for Saccade Latency

We aim to ask and answer an essential question "how quickly do we react after observing a displayed visual target?" To this end, we present psychophysical studies that characterize the remarkable disconnect between human saccadic behaviors and spatial visual acuity. Building on the results of our studies, we develop a perceptual model to predict temporal gaze behavior, particularly saccadic latency, as a function of the statistics of a displayed image. Specifically, we implement a neurologically-inspired probabilistic model that mimics the accumulation of confidence that leads to a perceptual decision. We validate our model with a series of objective measurements and user studies using an eye-tracked VR display. The results demonstrate that our model prediction is in statistical alignment with real-world human behavior. Further, we establish that many sub-threshold image modifications commonly introduced in graphics pipelines may significantly alter human reaction timing, even if the differences are visually undetectable. Finally, we show that our model can serve as a metric to predict and alter reaction latency of users in interactive computer graphics applications, thus may improve gaze-contingent rendering, design of virtual experiences, and player performance in e-sports. We illustrate this with two examples: estimating competition fairness in a video game with two different team colors, and tuning display viewing distance to minimize player reaction time.

cs.HC↗

arXiv2021

Efficient Dataflow Modeling of Peripheral Encoding in the Human Visual System

Computer graphics seeks to deliver compelling images, generated within a computing budget, targeted at a specific display device, and ultimately viewed by an individual user. The foveated nature of human vision offers an opportunity to efficiently allocate computation and compression to appropriate areas of the viewer's visual field, especially with the rise of high resolution and wide field-of-view display devices. However, while the ongoing study of foveal vision is advanced, much less is known about how humans process imagery in the periphery of their vision -- which comprises, at any given moment, the vast majority of the pixels in the image. We advance computational models for peripheral vision aimed toward their eventual use in computer graphics. In particular, we present a dataflow computational model of peripheral encoding that is more efficient than prior pooling - based methods and more compact than contrast sensitivity-based methods. Further, we account for the explicit encoding of "end stopped" features in the image, which was missing from previous methods. Finally, we evaluate our model in the context of perception of textures in the periphery. Our improved peripheral encoding may simplify development and testing of more sophisticated, complete models in more robust and realistic settings relevant to computer graphics.

cs.GR↗