Collaborating Authors

motion detection

Retinal waves prime visual motion detection by simulating future optic flow


As a mouse runs forward across the forest floor, the scenery that it passes flows backwards. Ge et al. show that the developing mouse retina practices in advance for what the eyes must later process as the mouse moves. Spontaneous waves of retinal activity flow in the same pattern as would be produced days later by actual movement through the environment. This patterned, spontaneous activity refines the responsiveness of cells in the brain's superior colliculus, which receives neural signals from the retina to process directional information. Science , abd0830, this issue p. [eabd0830][1] ### INTRODUCTION Fundamental circuit features of the mouse visual system emerge before the onset of vision, allowing the mouse to perceive objects and detect visual motion immediately upon eye opening. How the mouse visual system achieves self-organization by the time of eye opening without structured external sensory input is not well understood. In the absence of sensory drive, the developing retina generates spontaneous activity in the form of propagating waves. Past work has shown that spontaneous retinal waves provide the correlated activity necessary to refine the development of gross topographic maps in downstream visual areas, such as retinotopy and eye-specific segregation, but it is unclear whether waves also convey information that instructs the development of higher-order visual response properties, such as direction selectivity, at eye opening. ### RATIONALE Spontaneous retinal waves exhibit stereotyped changing spatiotemporal patterns throughout development. To characterize the spatiotemporal properties of waves during development, we used one-photon wide-field calcium imaging of retinal axons projecting to the superior colliculus in awake neonatal mice. We identified a consistent propagation bias that occurred during a transient developmental window shortly before eye opening. Using quantitative analysis, we investigated whether the directionally biased retinal waves conveyed ethological information relevant to future visual inputs. To understand the origin of directional retinal waves, we used pharmacological, optogenetic, and genetic strategies to identify the retinal circuitry underlying the propagation bias. Finally, to evaluate the role of directional retinal waves in visual system development, we used pharmacological and genetic strategies to chronically manipulate wave directionality and used two-photon calcium imaging to measure responses to visual motion in the midbrain superior colliculus immediately after eye opening. ### RESULTS We found that spontaneous retinal waves in mice exhibit a distinct propagation bias in the temporal-to-nasal direction during a transient window of development (postnatal day 8 to day 11). The spatial geometry of directional wave flow aligns strongly with the optic flow pattern generated by forward self-motion, a dominant natural optic flow pattern after eye opening. We identified an intrinsic asymmetry in the retinal circuit that enforced the wave propagation bias involving the same circuit elements necessary for motion detection in the adult retina, specifically asymmetric inhibition from starburst amacrine cells through γ-aminobutyric acid type A (GABAA) receptors. Finally, manipulation of directional retinal waves, through either the chronic delivery of gabazine to block GABAergic inhibition or the starburst amacrine cell–specific mutation of the FRMD7 gene, impaired the development of responses to visual motion in superior colliculus neurons downstream of the retina. ### CONCLUSION Our results show that spontaneous activity in the developing retina prior to vision onset is structured to convey essential information for the development of visual response properties before the onset of visual experience. Spontaneous retinal waves simulate future optic flow patterns produced by forward motion through space, due to an asymmetric retinal circuit that has an evolutionarily conserved link with motion detection circuitry in the mature retina. Furthermore, the ethologically relevant information relayed by directional retinal waves enhances the development of higher-order visual function in the downstream visual system prior to eye opening. These findings provide insight into the activity-dependent mechanisms that regulate the self-organization of brain circuits before sensory experience begins. ![Figure][2] Origin and function of directional retinal waves. ( A ) Imaging of retinal axon activity reveals a propagation bias in spontaneous retinal waves (scale bar, 500 μm). ( B ) Cartoon depiction of wave flow vectors projected onto visual space. Vectors (black arrows) align with the optic flow pattern (red arrows) generated by forward self-motion. ( C ) Asymmetric GABAergic inhibition in the retina mediates wave directionality. ( D ) Developmental manipulation of wave directionality disrupts direction-selective responses in downstream superior colliculus neurons at eye opening. The ability to perceive and respond to environmental stimuli emerges in the absence of sensory experience. Spontaneous retinal activity prior to eye opening guides the refinement of retinotopy and eye-specific segregation in mammals, but its role in the development of higher-order visual response properties remains unclear. Here, we describe a transient window in neonatal mouse development during which the spatial propagation of spontaneous retinal waves resembles the optic flow pattern generated by forward self-motion. We show that wave directionality requires the same circuit components that form the adult direction-selective retinal circuit and that chronic disruption of wave directionality alters the development of direction-selective responses of superior colliculus neurons. These data demonstrate how the developing visual system patterns spontaneous activity to simulate ethologically relevant features of the external world and thereby instruct self-organization. [1]: /lookup/doi/10.1126/science.abd0830 [2]: pending:yes

Swann Xtreem Wireless security camera review: Free cloud storage, motion detection, and solid hardware


Swann is best known for its professional, wired security systems, but lately it's been muscling its way into more consumer-friendly categories, like this straightforward offering. Of late, Swann has continued to move upmarket, and its latest home security camera, the Xtreem wireless, is designed to compete with some of the higher-end home systems available, such as Arlo. The hardware is compact and substantial (at 12 ounces, sans base), an all-white device that's weatherized for outdoor use. The small base can be attached to the wall via included screws; the camera snaps securely into place magnetically and allows for easy positioning. As the name implies, the camera is completely wireless.

Ring unveils the Floodlight Cam Wired Pro, with radar-powered bird's-eye view


Just a couple of months after Ring unwrapped its new, radar-enabled aerial view for the Video Doorbell Pro 2, the Amazon-owned smart brand is now rolling out the clever technology to its updated wired floodlight. At the same time, Ring says it's bringing a color version of its pre-roll video feature to a fourth generation of its battery-powered video doorbell. Slated to ship on May 6 for $250 (you can preorder starting today), the Ring Floodlight Cam Wired Pro will boast both Bird's-Eye View and 3D Motion Detection, a pair of features powered by radar rather than infrared motion sensors. Meanwhile, the Ring Video Doorbell 4 is set to arrive April 28 for $200, and it will add color to the pre-roll functionality that debuted on last year's Video Doorbell 3 Plus. An upgrade to 2019's well received Floodlight Cam, the revamped Floodlight Cam Wired Pro arrives with the same 1080p video resolution while adding HDR for a needed contrast boost, along with a 140-degree (horizontal) by 60-degree (vertical) field of view.

Ring Video Doorbell Pro 2 review: Radar delivers a birds-eye view


Who'd have thought that radar would become an increasingly important technology in the smart home? The second-gen Google Nest Hub taps the tech to track your sleep, and now the Ring Video Doorbell Pro 2 is using it for 3D motion detection. Ring's top-of-the-line doorbell camera offers other advanced features, too, but is it enough to justify its $250 price tag--and the subscription you'll need to access them? If you're not familiar with Ring's video doorbells and other home security cameras, you'll get motion and visitor alerts, but you'll only be able to view a live stream of what's happening in front of the camera unless you sign up for a Ring Protect subscription. You can talk to people in front of the camera--using your smartphone or an Echo Show smart display--but you won't be able to see events that occurred in the past. Ring's subscriptions aren't terribly expensive, starting at $3 per camera per month, but they're the only way to get motion-activated recordings that are stored in the cloud, so you can watch them later (you get up to 60 days of history).

Geometric Change Detection in Digital Twins using 3D Machine Learning Artificial Intelligence

Digital twins are meant to bridge the gap between real-world physical systems and virtual representations. Both stand-alone and descriptive digital twins incorporate 3D geometric models, which are the physical representations of objects in the digital replica. Digital twin applications are required to rapidly update internal parameters with the evolution of their physical counterpart. Due to an essential need for having high-quality geometric models for accurate physical representations, the storage and bandwidth requirements for storing 3D model information can quickly exceed the available storage and bandwidth capacity. In this work, we demonstrate a novel approach to geometric change detection in the context of a digital twin. We address the issue through a combined solution of Dynamic Mode Decomposition (DMD) for motion detection, YOLOv5 for object detection, and 3D machine learning for pose estimation. DMD is applied for background subtraction, enabling detection of moving foreground objects in real-time. The video frames containing detected motion are extracted and used as input to the change detection network. The object detection algorithm YOLOv5 is applied to extract the bounding boxes of detected objects in the video frames. Furthermore, the rotational pose of each object is estimated in a 3D pose estimation network. A series of convolutional neural networks conducts feature extraction from images and 3D model shapes. Then, the network outputs the estimated Euler angles of the camera orientation with respect to the object in the input image. By only storing data associated with a detected change in pose, we minimize necessary storage and bandwidth requirements while still being able to recreate the 3D scene on demand.

A Bioinspired Retinal Neural Network for Accurately Extracting Small-Target Motion Information in Cluttered Backgrounds Artificial Intelligence

Robust and accurate detection of small moving targets in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform search and tracking tasks. Inspired by the neural circuitry of elementary motion vision in the mammalian retina, this paper proposes a bioinspired retinal neural network based on a new neurodynamics-based temporal filtering and multiform 2-D spatial Gabor filtering. This model can estimate motion direction accurately via only two perpendicular spatiotemporal filtering signals, and respond to small targets of different sizes and velocities by adjusting the dendrite field size of the spatial filter. Meanwhile, an algorithm of directionally selective inhibition is proposed to suppress the target-like features in the moving background, which can reduce the influence of background motion effectively. Extensive synthetic and real-data experiments show that the proposed model works stably for small targets of a wider size and velocity range, and has better detection performance than other bioinspired models. Additionally, it can also extract the information of motion direction and motion energy accurately and rapidly.

Nooie's new smart cam offers 360 degrees of security for a steal

USATODAY - Tech Top Stories

The Nooie Cam 360 has a rotating, high-def camera that automatically tracks you as you move about the room. Here are the Nooie Cam 360's specs: The Nooie Cam 360 is a budget-friendly indoor home security camera that features motion tracking and, as the name implies, 360-degree rotation. The camera is equipped with a 1080p high-def lens and two 940nm infrared LEDs. It has other smart camera features like two-way audio functionality, night vision, and a status light indicator that can be toggled on or off. Nooie smart alerts are sent when the camera detects sound or motion.

Disney imagineers reveal creepy skinless robot with realistic eyes and teeth

Daily Mail - Science & tech

Disney specializes in bringing imagination to life, but its latest innovation takes this idea one step further – a robot designed with a realistic and interactive stare. The company's imagineers unveiled a skinless humanoid animatronic bust, complete with movable eyes, eyelids and brows to create a human-like gaze. The robot is fitted with a chest-mounted sensor that uses motion detection to determine when a guest is attempting to engage, which activates a series of motors that control interactions. The motors are layered to allow for movements such as breathing, blinking and saccades to'create increasingly complex and life-like behaviors.' Walt Disney started'The Walt Disney Company' 97 years ago in a small Los Angeles office.

Get the Ring Door View Cam for half-price in Amazon Prime Day sale 2020

Daily Mail - Science & tech

There are some fantastic discounts to be found on the latest tech gadgets this Amazon Prime Day 2020. If you've been toying with investing in some smart home security but are not sure where to start, then why not invest in the top-rated wireless doorbell camera from Ring? The Ring Door View Cam is now an impressive 50 per cent off on Amazon - reduced to a very enticing £59. With over 1,200 reviews and an average rating of 4.4 out of 5, it comes highly recommended from shoppers and is an affordable way to jump into the smart home security scene. A video doorbell is the latest way to protect your home, allowing you to screen you visitors and see who's knocking even when you're not in.

Ring's second-gen video doorbell is loaded with useful features

USATODAY - Tech Top Stories

If it feels like Ring is rolling out one new doorbell after another, you're not wrong. Earlier this year, the smart home company introduced the Ring Video Doorbell 3 and Ring Video Doorbell 3 Plus. In addition to those new models, Ring released the new and improved second-generation Ring Video Doorbell--an upgrade from the first doorbell Ring released in 2014. Smart doorbell cameras have come a long way over the last six years, so it makes sense that Ring revised its most affordable smart doorbell with 1080p resolution (up from 720p), clearer and crisper night vision, and loud, easy to-understand two-way audio. The Ring Video Doorbell (second-generation) maintains the same look and feel of other Ring doorbell cameras.