Video Breakthroughs
Follow
Find tag "algorithms"
147.7K views | +105 today
Video Breakthroughs
Monitoring innovations in post-production, head-end, streaming, OTT, second-screen, UHDTV, multiscreen strategies & tools
Curated by Nicolas Weil
Your new post is loading...
Your new post is loading...
Scooped by Nicolas Weil
Scoop.it!

Why wait for bandwidth savings from HEVC, Crunch AVC 50% today!

Why wait for bandwidth savings from HEVC, Crunch AVC 50% today! | Video Breakthroughs | Scoop.it

The digital video industry seems to be gradually succumbing to the allure of the 50% bandwidth savings promised by HEVC, aka h.265. What if those savings can be achieved with the existing AVC, h.264, technology? Cinova thinks its post-processing product, Crunch, can do just that.

The benefits the video industry can realize from a reduction of 50% in the amount of bandwidth necessary to deliver video are enormous. From saving money in bandwidth charges to delivering higher quality video on mobile networks, there are few places in the chain of delivery that don’t benefit in some way.

However, the cost and time required to move to a new codec, like HEVC, are similarly enormous. Devices such as televisions, set-top boxes and smartphones need to be replaced, video encoders upgraded, not to mention all the video that needs to be re-encoded in the new format. The change from MPEG2 encoding to AVC based MPEG4 took the better part of a decade. Likely, HEVC adoption will take a similar length of time.

Sunil Sanghavi, COO of Cinova, believes there is a lot more efficiency to be wrung out of AVC, and that it will get us to 50% savings right now.

more...
NanoTech Entertainment's curator insight, May 18, 2:40 PM

HEVC far from mainstream.

Scooped by Nicolas Weil
Scoop.it!

BBC R&D White Paper : Scene Segmentation using Multiple Metrics

BBC R&D White Paper : Scene Segmentation using Multiple Metrics | Video Breakthroughs | Scoop.it

Video scene segmentation is often regarded as a primary step with regards to analysis of video data. The process of scene segmentation involves partitioning a video stream into scenes in which each scene is comprised of frames of similar content. This work may form a primary stage of larger system for automated quality control and image restoration that may be conducted in the BBC

more...
No comment yet.
Scooped by Nicolas Weil
Scoop.it!

IBC 2013: Beamr promises to shave 40% off OTT bit-rates

IBC 2013: Beamr promises to shave 40% off OTT bit-rates | Video Breakthroughs | Scoop.it

Imaging technology Beamr demonstrated a video optimisation solution at IBC 2013 that can potentially reduce bit-rates by up to 40% for streamed OTT video.

Bit-rates from physical media such as BluRay discs could be reduced by up to 75%, the company also claimed.

 

Beamr’s CTO, Dror Gill, emphasised that Beamr Video is not a new type of video compression codec: instead it controls existing video compression systems like H.264 or HEVC, manipulating the encoding process in such a way that, in effect, it lowers the threshold at which bit-rate reductions cause artefacts visible to the naked eye.

more...
No comment yet.
Scooped by Nicolas Weil
Scoop.it!

Skin tone macroblock detection for video coding can improve the perceptual quality of human faces

Skin tone macroblock detection for video coding can improve the perceptual quality of human faces | Video Breakthroughs | Scoop.it

In video compression algorithms, the quantization parameter is typically adapted based on overall bit usage and relative complexity of the region in the picture. However, such complexity-based rate control algorithms do not emphasize the fact that certain objects, such as human faces, are more sensitive to the overall perceptual video quality. To improve overall perceptual quality, it is important to classify human faces as regions of interest (ROI) and preserve as much detail as possible. The challenge is to develop a reliable algorithm that works in real-time implementations. This article will explore a low-complexity system that can run on a single-core DSP as part of an encoder implementation.

 

The proposed system is a low-complexity, color-based skin tone detection, which classifies skin tone macroblocks (MB) as ROI MBs and non-skin tone macroblocks as non-ROI MBs (MB; 16 × 16 block of pixels). The classification is based on some empirical thresholds applied to the mean of the color components. The empirical threshold values were defined after an extensive training using material that covers all kinds of races. According to this classification and a modified rate control (RC) that permits smoothly assigning different levels of quality, we can increase visual quality in human faces.

more...
No comment yet.