Remote Photoplethysmography (rPPG) detects heartbeat-induced skin color changes via camera to extract the Blood Volume Pulse (BVP) signal, which helps measure vital signs like heart and respiratory rates. Despite its ...
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Remote Photoplethysmography (rPPG) detects heartbeat-induced skin color changes via camera to extract the Blood Volume Pulse (BVP) signal, which helps measure vital signs like heart and respiratory rates. Despite its popularity in health research for its user-friendly and noninvasive approach, rPPG's BVP signal quality can be compromised by factors like videocompression. This research seeks to evaluate how various compression methods affect BVP signal quality, aiming to enhance rPPG's practical use. We created the ZJXU-MOTION dataset to assess videocompression's impact on Blood Volume Pulse (BVP) signal quality during motion, considering activity and lighting. We compared common codecs like H.264, H.265, AV1/VP9, MJPEG, ProRes, and FFV1, analyzing how compression artifacts and bitrates influence BVP. Our results were confirmed with the UBFC-Phys dataset. Inter-frame compression can degrade BVP signal quality by adding noise. For clear signals, use intra-frame compression like H.265 with a GOP size of 1. If using inter-frame, keep GOP small and CQP stable. For static videos, H.265 CQP or VP9 VBR with GOP sizes of 1-3 work well. For low-motion videos, H.265 provides better performance. For complex motion, lossless compression methods like FFV1 outperform H.264 and H.265 in preserving BVP signal quality. Given that inter-frame compression introduces noise into BVP processing, we recommend intra-frame compression - particularly H.265 with a GOP of 1 - for optimal signal extraction. For complex motion, H.265 and FFV1 offer robust solutions, with FFV1 being especially effective in high-motion conditions. These findings are instrumental for advancing rPPG technology in health monitoring and diagnostics.
Due to the increasing number of new services and devices that allow the creation, distribution and consumption of video content, the amount of video information being transmitted all over the world is constantly growi...
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Due to the increasing number of new services and devices that allow the creation, distribution and consumption of video content, the amount of video information being transmitted all over the world is constantly growing. videocompression technology is essential to cope with the ever increasing volume of digital video data being distributed in today's networks, as more e cient videocompression techniques allow support for higher volumes of video data under the same memory/bandwidth constraints. This is especially relevant with the introduction of new and more immersive video formats associated with signi cantly higher amounts of data. In this thesis, novel techniques for improving the e ciency of current and future video coding technologies are investigated. Several aspects that in uence the way conventional video coding methods work are considered. In particular, the properties and limitations of the Human Visual System are exploited to tune the performance of video encoders towards better subjective quality. Additionally, it is shown how the visibility of speci c types of visual artefacts can be prevented during the video encoding process, in order to avoid subjective quality degradations in the compressed content. Techniques for higher videocompression e ciency are also explored, targeting to improve the compression capabilities of state-of-the-art video coding standards. Finally, the application of video coding technologies to practical use-cases is considered. Accurate estimation models are devised to control the encoding time and bit rate associated with compressed video signals, in order to meet speci c encoding time and transmission time restrictions.
With recent advances in computing and communication technologies, ubiquitous access to high quality multimedia content such as high definition video using smartphones, netbooks, or tablets is a fact of our daily life....
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With recent advances in computing and communication technologies, ubiquitous access to high quality multimedia content such as high definition video using smartphones, netbooks, or tablets is a fact of our daily life. However, power consumption is still a major concern for portable devices. One approach to address this concern is to control and optimize power consumption using a power model for each multimedia application, such as a video decoder. In this paper, a generic, comprehensive and granular decoder complexity model for the baseline profile of H.264/AVC decoder has been proposed. The modeling methodology was designed to ensure a platform and implementation independent complexity model. Simulation results indicate that the proposed model estimates decoder complexity with an average accuracy of 92.15% for a wide range of test sequences using both the JM reference software and the x264 software implementation of H.264/AVC, and 89.61% for a dedicated hardware implementation of the motion compensation module. It should be noted that in addition to power consumption control, the proposed model can be used for designing a receiver-aware H.264/AVC encoder, where the complexity constraints of the receiver side are taken into account during compression. To further evaluate the proposed model, a receiver-aware encoder has been designed and implemented. Our simulation results indicate that using the proposed model the designed receiver aware encoder performs similar to the original encoder, while still being able to satisfy the complexity constraints of various decoders. (C) 2014 Elsevier Inc. All rights reserved.
Many useful DSP algorithms have high dimensions and complex logic. Consequently, an efficient implementation of these algorithms on parallel processor arrays must involve a structured design methodology. Full-search b...
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Many useful DSP algorithms have high dimensions and complex logic. Consequently, an efficient implementation of these algorithms on parallel processor arrays must involve a structured design methodology. Full-search block-matching motion estimation is one of those algorithms that can be developed using parallel processor arrays. In this paper, we present a hierarchical design methodology for the full-search block matching motion estimation. Our proposed methodology reduces the complexity of the algorithm into simpler steps and then explores the different possible design options at each step. Input data timing restrictions are taken into consideration as well as buffering requirements. A designer is able to modify system performance by selecting some of the algorithm variables for pipelining or broadcasting. Our proposed design strategy also allows the designer to study time and hardware complexities of computations at each level of the hierarchy. The resultant architecture allows easy modifications to the organization of data buffers and processing elements-their number, datapath pipelining, and complexity-to produce a system whose performance matches the video data sample rate requirements.
In this paper, we present two novel disk failure recovery methods that utilize the inherent characteristics of video streams for efficient recovery. Whereas the first method exploits the inherent redundancy in video s...
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In this paper, we present two novel disk failure recovery methods that utilize the inherent characteristics of video streams for efficient recovery. Whereas the first method exploits the inherent redundancy in video streams (rather than error-correcting codes) to approximately reconstruct data stored on failed disks, the second method exploits the sequentiality of video playback to reduce the overhead of online failure recovery in conventional RAID arrays. For the former approach, we present loss-resilient versions of JPEG and MPEG compressionalgorithms. We present an inherently redundant array of disks (IRAD) architecture that combines these loss-resilient compressionalgorithms with techniques for efficient placement of video streams on disk arrays to ensure that on-the-fly recovery does not impose any additional load on the array. Together, they enhance the scalability of multimedia servers by (1) integrating the recovery process with the decompression of video streams, and thereby distributing the reconstruction process across the clients;and (2) supporting graceful degradation in the quality of recovered images with increase in the number of disk failures. We present analytical and experimental results to show that both schemes significantly reduce the failure recovery overhead in a multimedia server.
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