Motion estimation (ME) is a computation and data intensive module in video coding system. The search window reuse methods play a critical role in bandwidth reduction by exploiting the data locality in video coding sys...
详细信息
Motion estimation (ME) is a computation and data intensive module in video coding system. The search window reuse methods play a critical role in bandwidth reduction by exploiting the data locality in video coding system. In this paper, a search window reuse method (Level C+) is proposed for MPEG-2 to H.264/AVC transcoding. The proposed method is designed for ultra-low bandwidth application, while the on-chip memory is not a main constraining factor. By loading search window for the motion estimation unit (MEU) and applying motion vector clipping processing, each MB in MEU can utilize both horizontal and vertical search reuse. A very low bandwidth level (R-alpha < 2) can be achieved with an acceptable on-chip memory.
We present a two-level rate control approach for VC-1 to H.264 transcoding. First, a low complexity algorithm in which the key is to find the relationship between quantization parameters (QPs) in VC-1 to QPs in H.264....
详细信息
ISBN:
(纸本)9781424456536
We present a two-level rate control approach for VC-1 to H.264 transcoding. First, a low complexity algorithm in which the key is to find the relationship between quantization parameters (QPs) in VC-1 to QPs in H.264. Second, a medium complexity algorithm in which the key is to use mean absolute differences and sum of absolute transform differences calculated in VC-1 to estimate the complexity of macroblocks in H.264 for a pixel/transform domain transcoder. The low complexity rate control tool has a limitation of only able to rate-control transcode for QP ranges from 10 to 29. To transcode the entire QP range we propose a combination of low and median complexities tools. Results show that the proposed rate control transcoding is less complex than that of a full-cascaded transcoder with regular rate control turned on, while maintaining target bit-rate and PSNR.
As for down-sizing MPEG-2 to H.264/AVC transcoding, an efficient algorithm of estimating initial H.264/AVC motion vectors is proposed. By using the estimated initial motion vectors, only a small range of motion vector...
详细信息
ISBN:
(纸本)9781424456536
As for down-sizing MPEG-2 to H.264/AVC transcoding, an efficient algorithm of estimating initial H.264/AVC motion vectors is proposed. By using the estimated initial motion vectors, only a small range of motion vector refinement is sufficient to find the final motion vector for each partition. Experimental results show that our proposed algorithm achieves average 0.08 dB improvement (maximum 0.24 dB) in the picture quality compared to the other state-of-art method. At the same time, the computational complexity of estimating the initial motion vectors is less than that of the other state-of-art technique (average 36% reduction).
In this paper, we present a novel technique to transcode VC-I to H.264 high profile (HP). We use the low frequency AC coefficients to estimate the homogeneity of the block to predict the block transform size and use t...
详细信息
ISBN:
(纸本)9781424438273
In this paper, we present a novel technique to transcode VC-I to H.264 high profile (HP). We use the low frequency AC coefficients to estimate the homogeneity of the block to predict the block transform size and use the magnitude of the motion vectors to help decide transcoding mode for interlaced video. We also analyze the drift error specific to transcoding VC-I to H.264 and apply this study results to improve final video quality. Implementation of the solution shows that the complexity of the transcoder, when compared to a full-cascaded transcoder, is greatly reduced without a significant loss in peak-signal-to-noise ratio (PSNR).
The emerging video coding standard, HEVC, was developed to replace the current standard, H.264/AVC. However, in order to promote inter-operability with existing systems using the H.264/AVC, transcoding from H.264/AVC ...
详细信息
ISBN:
(纸本)9781479923427
The emerging video coding standard, HEVC, was developed to replace the current standard, H.264/AVC. However, in order to promote inter-operability with existing systems using the H.264/AVC, transcoding from H.264/AVC to the HEVC codec is highly needed. This paper presents a transcoding solution that uses machine learning techniques in order to map H.264/AVC macroblocks into HEVC coding units (CUs). Two alternatives to build the machine learning model are evaluated. The first uses a static training, where the model is built offline and used to transcode any video sequence. The other uses a dynamic training, with two well-defined stages: a training stage and a transcoding stage. In the training stage, full re-encoding is performed while the H.264/AVC and the HEVC information are gathered. This information is then used to build a model, which is used in the transcoding stage to classify the HEVC CU partitioning. Both solutions are tested with well-known video sequences and evaluated in terms of rate-distortion (RD) and complexity. The proposed method is on average 2.26 times faster than the trivial transcoder using fast motion estimation, while yielding a RD loss of only 3.6% in terms of bitrate.
Summary form only given. Common e-commerce websites rely heavily on JPEG images for product presentation. In this paper we present a new coding scheme and file format that is tailored to the presentation of single-col...
详细信息
ISBN:
(纸本)9781467360371
Summary form only given. Common e-commerce websites rely heavily on JPEG images for product presentation. In this paper we present a new coding scheme and file format that is tailored to the presentation of single-color products. A JPEG image file can be transcoded into this new format leading to substantial reduction in file size (Average of 28%) with practically no quality degradation. We describe how we can take advantage of several features found in images for product presentation to improve coding efficiency. Objective and subjective performance measurements are presented to demonstrate that little quality degradation is incurred after transcoding.
MXF standards SMPTE ST 377-1:2011 and ST 422:2006; SMPTE Technical Committee TC-31FS AHG ST 422 Revision (JPEG2000 in MXF); the Advanced Media Workflow Association; and related SMPTE standards all clarify MXF implemen...
详细信息
ISBN:
(纸本)9781629938370
MXF standards SMPTE ST 377-1:2011 and ST 422:2006; SMPTE Technical Committee TC-31FS AHG ST 422 Revision (JPEG2000 in MXF); the Advanced Media Workflow Association; and related SMPTE standards all clarify MXF implementations for the most active use cases. To illustrate technical advances, this paper presents laboratory observations of MXF video clips from multivendor sources alongside mathematically generated test patterns, master- and archival-grade video content, and an MXF metadata viewer. The paper focuses especially on reformatting JPEG2000, uncompressed, AVI, and MOV master/archive files into MXF for interchange and preservation. Video clips are shown.
Watching Same Content on Three-Screen TV Continuously (WSC3STVC) has been considered as one of the representative services in smart homes recently. This service offers content mobility among multiple kinds of screens ...
详细信息
Watching Same Content on Three-Screen TV Continuously (WSC3STVC) has been considered as one of the representative services in smart homes recently. This service offers content mobility among multiple kinds of screens based on user position in home. Quality of Experience (QoE) and service implementation cost are two important challenges for supporting WSC3STVC service. To the best of our knowledge, there is no visible attempt to design a comprehensive platform for supporting this service in smart homes. Benefiting from cloud computing, peer-to-peer (P2P) network, clustering and H.264 SVC transcoding, this paper proposes a QoE-aware and cost-effective platform for supporting WSC3STVC service in smart home. The strong points of the proposed platform are transcoding in cloud instead of Home GateWay (HGW) for decreasing HGW cost, content switching inside HGW for reducing service delay, using a cloud-managed P2P network for improving bandwidth between cloud and homes and also clustering homes for reducing transfer delay between homes.
Scalable Video Coding (SVC) is backwards compatible to H.264/AVC in the sense that the base layer sub-bitstream is decodable by an H.264/AVC decoder. However, there are applications wherein it is desirable for an H.26...
详细信息
ISBN:
(纸本)9781424442904
Scalable Video Coding (SVC) is backwards compatible to H.264/AVC in the sense that the base layer sub-bitstream is decodable by an H.264/AVC decoder. However, there are applications wherein it is desirable for an H.264/AVC decoder to obtain a higher resolution video representation than the base layer within SVC. In order to fulfill the needs of such application scenarios, transcoding of SVC enhancement layers to H.264/AVC is required. This paper presents a transcoding scheme that is capable of transcoding a spatial scalable SVC bitstreams to H.264/AVC bitstreams that provide high resolution than the H.264/AVC compliant base layer. To reduce the complexity at the transcoder, a fast mode decision (MD) process is proposed, wherein the original SVC macroblock coding modes and motion information are reused as much as possible. Experimental results show that proposed scheme performs elegantly compared with full-decoding-and-encoding transcoding with low computational complexity.
Internet services are becoming more ubiquitous and 3D graphics is increasingly gaining a strong foothold in the Web technology domain. Recently, with WebGL, real-time 3D graphics in the Browser became a reality and mo...
详细信息
Internet services are becoming more ubiquitous and 3D graphics is increasingly gaining a strong foothold in the Web technology domain. Recently, with WebGL, real-time 3D graphics in the Browser became a reality and most major Browsers support WebGL natively today. This makes it possible to create applications like 3D catalogs of artifacts, or to interactively explore Cultural Heritage objects in a Virtual Museum on mobile devices. Frameworks like the open-source system X3DOM provide declarative access to low-level GPU routines along with seamless integration of 3D graphics into HTML5 applications through standardized Web technologies. Most 3D models also need to be optimized to address concerns like limited network bandwidth or reduced GPU power on mobile devices. Therefore, recently an online platform for the development of Virtual Museums with particular attention to presentation and visualization of Cultural Heritage assets in online virtual museums was proposed [1]. This common implementation Framework (CIF) allows the user to upload large 3D models, which are subsequently converted and optimized for web display and embedded in an HTML5 application that can range from simple interactive display of the model to an entire virtual environment like a virtual walk-through. Generating these various types of applications is done via a templating mechanism, which will be further elaborated within this paper. Moreover, to efficiently convert many large models into an optimized form, a substantial amount of computing power is required, which a single system cannot yet provide in a timely fashion. Therefore, we also describe how the CIF can be used to utilize a dynamically allocated cloud-based or physical cluster of commodity hardware to distribute the workload of model optimization for the Web.
暂无评论