Vision 4 Live

[Jon Levatte]

TheKnight Vision co-curricular program tells the Wartburg story by providing meaningful hands-on learning opportunities for our students to create quality content that educates, entertains, and engages our audience. Knight Vision reaches more than 48,000 viewers each year. Students from any major are encouraged to become paid staff members. Each year the Knight Vision staff produces more than 200 live programs and works with state-of-the-art equipment and a new HD control room.

For best quality streaming, we do recommend watching via a high-speed internet connection. For best results, a wired connection is preferred. Viewers watching over 3G or 4G cellular networks may encounter buffering or streaming delays. For questions, comments, or streaming questions, contact knight...@wartburg.edu

Wartburg is a selective liberal arts college of the Lutheran church (ELCA) and internationally recognized for community engagement. Wartburg College is dedicated to challenging and nurturing students for lives of leadership and service as a spirited expression of their faith and learning.

In the relatively new, ever-changing arena of High Dynamic Range (HDR) technologies, there are quite a few options to consider when it comes to creating video content with rich, beautiful, pronounced pictures with both brighter and darker colors. These include HDR10, HDR10+, HLG, and Dolby Vision. This post focuses on the key benefits of Dolby Vision, and how to configure a Dolby Vision enabled stream using AWS Elemental Live encoders.

Dolby Vision is an HDR technology built by Dolby Laboratories, Inc. Its key differentiator versus other HDR formats is the use of dynamic metadata. This metadata, present in every video frame, allows video displays that support Dolby Vision to map the video accurately, consistently and efficiently to the capabilities of the panel itself. This delivers an optimal result in terms of color accuracy, along with more accurate bright and dark area rendering on-screen. HDR10, in contrast, uses a static metadata implementation, which limits the contrast and color accuracy a viewer experiences compared to watching in Dolby Vision. Using a 10-bit color depth on AWS Elemental Live with Dolby Vision unlocks a possible 10 billion colors vs. the Rec 709 8-bit that uses only 16.7 million possible colors.

Through a software license on your AWS Elemental Live encoder, deploying this technology is simple. The functionality raises the bar of the viewership experience and removes the need to purchase extra hardware for Dolby Vision processing.

AWS Elemental Live is a robust, feature-rich, on-premises appliance that performs advanced encoding, transcoding, and other stream conditioning functions, including Dolby Vision stream processing. At a high level, a Dolby Vision stream is composed of the HEVC encoded stream with the addition of Dolby metadata. The metadata is carried as RPU (reference processing unit) sub-stream, which is the frame-by-frame dynamic metadata, stored in private MPEG NAL (network abstraction layer) units. AWS Elemental Live analyzes the HDR input video, generates Dolby Vision dynamic metadata, packages that metadata into RPU format and muxes it with the HEVC elementary stream.

AWS Elemental Live supports Dolby Vision color space conversion for Profile 5 and Profile 8.1. Dolby Vision profiles define how a Dolby Vision stream is encoded for distribution, and includes the video codec, codec parameters, bit depth and how the RPU data is carried in the elementary video stream. Profile 5 is a Dolby Vision-only profile encoded using HEVC, while profile 8.1 is Dolby Vision with HDR10 cross-compatibility also encoded using HEVC.

The following configuration guide covers general prerequisites, requirements, and step-by-step instructions to set up an event with Dolby Vision enabled. It also demonstrates how to verify that Dolby Vision stream conditioning is taking place through the messages.

Dolby Vision is supported in the latest media devices like TVs, setup-boxes, phones, and PCs. The following example was encoded by the AWS Elemental Live encoder and shows a comparison of Dolby Vision vs SDR content played by an iPhone 12.

Dolby Vision is a compelling HDR technology designed to deliver an optimized and consistent experience on a consumer device. Using the preceding steps to configure your AWS Elemental Live encoder you are on your way to building a truly beautiful, high quality workflow. Setting up your AWS Elemental Live encoder takes only a few simple steps: satisfy the prerequisite requirements on the encoder, create your event, and validate Dolby Vision encode is taking place through a quick log check. We encourage you to explore the incredibly rich, vibrant video streams you can create using the method above. To learn more visit: -live/.

Would greatly appreciate it if this could be enabled in the built-in image/PDF viewer, even just at the level of allowing its use for quick text selection, copy-and-paste, as you presently can do from the Preview app (on Mac OS) or from the built-in document viewer on iOS.

I use it with a keyboard maestro macro to extract the text from images to the clipboard. It is actually quite good. For the few languages it supports, it is certainly the best option available. I used it in texts where ABBYY, Adobe and Tesseract had done a poor job and it was flawless nearly all the time. I am not sure it would work for adding a text layer to a pdf file though.

And just for the heck of it, sample some JavaScript code that uses the vision framework for text recognition. I tried that with 2 JPEGs, i.e. real fotos. Not with any PDFs yet. The script can be run with osascript -l JavaScript \ or copy/pasted into Script Editor and run there.

I tried it out with a JPEG that was converted from PDF in Preview, and the results where actually quite good. Only a table derailed it a bit, but that is to be expected. So the script could be used for OCR, but it would require amendments for PDFs: They usually consist of more than one page, and the script would have to loop over all pages, converting each one to a NSImage object and then running character recognition on it.

Whilst the new function is definitely much better than me having to re-write the text manually, I have found two (very minor) bugbears which could swiftly become irritating if applied to large numbers of documents:

Second, Abbyy (yes, two y) supports a lot more languages than Vision (see swift - Which languages are available for text recognition in Vision framework? - Stack Overflow and -us/articles/360017231600-OCR-Recognition-Languages). There is more than English, and Vision does not even do Japanese or Korean, nor Russian. Not even Portuguese as used in Portugal, BTW.

I would be happy, if DT would check for upcoming updates all technical possibilities, that are possible for DT. Of course, that are only my few cents on this topic, but it really makes sense to look for this very detailed.

I am now for over 30 years journalist and editor. So I work my whole day with words and paragraphs. By history such text based files are the strength of DT, not image or video etc. But as more research goes from text to all media types (multimedia) in the last decade(s) even in traditional media markets (newspapers etc), as more I found myself in the position of searching solutions to get text content out of non-text media (video, images etc).

By the years it was getting more and more important for my research to have text from of non-text media, because text has still the most strong search possibilities. And of course all ways of extracting text, that are automatic as most as possible, are the most helpful. And automation with text based files is a key strength of DT.

Therefore I would appreciate it very much, if all new possibilities of such automatic implementation, would be discussed here very deep and open-minded. Because they belong to the presence and to the future of text based research.

Multimedia is the future, perhaps the present. Tools for storing reference, annotating and researching must be able to deal with more than just text base documents in order to remain useful and relevant.

I have about 30,000 page images in formats including 1-bit TIFF (scanned from microfilm), JPG, and PNG. Since upgrading to Ventura (13.0) I have been noticing that a Finder search (that uses Spotlight) will bring up images with the word or phrase that is typed, typeset, or many handwritten cursive or block character images.

What I have found is that this is related to Spotlight and so far it seems that it must be on the internal SSD (2 TB) drive of my MacBook Pro (2020, Intel 6-core i7). An external SSD is not indexed by Spotlight.

A conversation today with two levels of Apple support indicates that this is a feature in development and it is not well documented either internally or for developer or public consumption. Nevertheless, it is in the system, even for Intel Macs, and seems to work reasonably well.

IrisVision Live offers handsfree magnification using breakthrough low vision technology. It can allow those with a visual impairment to watch TV, see family and friend's faces, cook, play music etc. again.

Demonstrations have proven that for many users this helps compensate for both central (Macular Degeneration) and peripheral (Retinitis Pigmentosa) vision loss extremely effectively. It even converts printed text to speech, allows users to watch YouTube videos directly via a Wi-Fi connection and responds to voice commands.

As a consultant ophthalmologist who has seen this device in use by a patient in March 2022 with bilateral macular dystrophy I was most impressed with the technology. I also tried it on myself. I have no connections with the manufacturers.

With live streaming on FC Vision, fleet managers have access to a real-time view of drivers and road conditions to identify potential risks, provide live coaching and proactive safety monitoring. Live streaming provides visibility into risky behaviors, such as drowsy or distracted driving. If a driver has received multiple alerts within a specified time, the dispatcher or fleet manager can check in with the driver to ensure they are safe and adhering to policies and best practices. Powering best-in-class visibility into fleet safety, Fleet Complete now also offers package options that include up to 100 minutes of streaming per device per month.

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