It is well observed that the nonzero transform coefficients for block-based hybrid video coding is more clustered in the low frequency region while more scattered in the high frequency region. Based on this observation, hybrid variable length coding (HVLC) was recently proposed, which divides each transform block into low frequency (LF) region and high frequency (HF) region by a pre-defined breakpoint and encodes the clustered low frequency coefficients with new coding schemes, such as two dimensional position and one-dimensional amplitude coding (2DP1DA) or three-dimensional position and amplitude coding (3DPA). However, the transition between clustered and scattered nonzero coefficients varies with different blocks and sequences. In this paper, we propose a context-adaptive hybrid variable length coding (CAHVLC) scheme, where multiple code tables are used and the code table is adaptively chosen based on the derivable context information from coded neighboring blocks or from the coded portion of the currently being coded block. The experimental results show that CAHVLC achieves about 6.5% ∼ 8% bit rate reduction for a wide range of quantization parameters (QP) compared with CAVLC in H.264.

Hybrid variable length coding (HVLC) was recently proposed as a novel entropy coding scheme for block-based image and video compression, which divides each transform block into low frequency (LF) region and high frequency (HF) region and codes them differently. To efficiently code LF region, a two-dimensional position and one-dimensional amplitude coding scheme (2DP1DA) was also proposed, which jointly codes the 2D position information, i.e., run of consecutive zero-valued coefficients and run of consecutive nonzero coefficients. To further explore the potential of HVLC concept, we propose a new scheme for coding LF region, which codes the 2D position and amplitude information of each nonzero cluster jointly with manageable complexity. The experimental results show that compared with CAVLC in H.264, about 3.5% bit rate reduction is achieved by the proposed method for a wide range of quantization parameters (QP).

Hybrid variable length coding (HVLC) was recently proposed as a novel entropy coding scheme for block-based image and video compression, which divides each transform block into low frequency (LF) region and high frequency (HF) region and codes them differently. To take advantage of the clustered nature of the nonzero coefficients in the LF region, a two-dimensional position and one-dimensional amplitude coding scheme (2DP1DA) was also proposed, which codes the 2D position information, i.e., run of consecutive zero-valued coefficients and run of consecutive nonzero coefficients, jointly by a 2D code table. To further improve the coding efficiency, joint position and amplitude coding is desirable. In this paper, we propose a three-dimensional position and amplitude coding scheme (3DPA) to jointly code the position and amplitude information for each nonzero cluster by a 3D code table. The experimental results show that HVLC with 3DPA for coding LF region achieves about 3.2%~3.7% bit rate reduction for a wide range of quantization parameters (QP) compared with CAVLC in H.264. Moreover, the 3DPA scheme is a compact way to realize the joint position and amplitude coding and it is very suitable for context-adaptive HVLC design.

Hybrid variable length coding (HVLC) was recently proposed as a novel entropy coding scheme for block-based image and video compression, which divides each transform block into low frequency (LF) region and high frequency (HF) region and codes them differently. To take advantage of the clustered nature of the nonzero coefficients in the LF region, a two-dimensional position and one- dimensional amplitude coding scheme (2DP1DA) was also proposed, which codes the 2D position information, i.e., run of consecutive zero-valued coefficients and run of consecutive nonzero coefficients, jointly by a 2D code table. To further improve the coding efficiency, joint position and amplitude coding is desirable. In this paper, we propose a three-dimensional position and amplitude coding scheme (3DPA) to jointly code the position and amplitude information for each nonzero cluster by a 3D code table. The experimental results show that HVLC with 3DPA for coding LF region achieves about 3.2%~3.7% bit rate reduction for a wide range of quantization parameters (QP) compared with CAVLC in H.264. Moreover, the 3DPA scheme is a compact way to realize the joint position and amplitude coding and it is very suitable for context-adaptive HVLC design.

The efficient progressive transmission of a textured 3D model, which has a texture image mapped on a geometric mesh, requires careful organization of the bit stream to quickly present high-resolution visualization on the user's screen. Bit rates for the mesh and the texture need to be properly balanced so that the decoded model has the best visual fidelity during transmission. This problem is addressed in the paper, and a bit allocation framework is proposed. In particular, the relative importance of the mesh geometry and the texture image on visual fidelity is estimated using a fast quality measure (FQM). Optimal bit distribution between the mesh and the texture is then computed under the criterion of maximizing the quality measured by FQM. Both the quality measure and the bit allocation algorithm are designed with low computation complexity. Empirical studies show that not only the bit allocation framework maximizes the receiving quality of the textured 3D model, but also it does not require sending additional information to indicate bit boundaries between the mesh and the texture in the multiplexed bit stream, which makes the streaming application more robust to bit errors that may occur randomly during transmission.

The conventional run-level variable length coding (RL-VLC), commonly adopted in block-based image and video compression to code quantized transform coefficients, is not efficient in coding consecutive nonzero coefficients. To overcome the deficiency, hybrid variable length coding (HVLC) is proposed in this paper. HVLC takes advantage of the clustered nature of nonzero transform coefficients in the low-frequency (LF) region and the scattered nature of nonzero transform coefficients in the high-frequency (HF) region by employing two types of VLC schemes. A novel two-dimensional position and one-dimensional amplitude coding scheme is proposed to code the LF coefficients while RL-VLC or an equivalent VLC scheme is retained to code the HF coefficients. Experimental results show that HVLC greatly favors the coding of high-resolution, high-complexity scenes, while it preserves low computational complexity.

Hybrid variable length coding (HVLC) was recently proposed as a novel entropy coding scheme for block-based image and video compression, in observation of the inefficiency of the conventional run-level variable length coding scheme in coding consecutive nonzero transform coefficients. In HVLC, each transform block is partitioned into low-frequency and high-frequency regions, and the coefficients in the two regions are coded separately by different schemes. The partition of the transform block was performed based on a predefined, constant breakpoint. In this paper, we propose to partition the transform block using a variable breakpoint that is adaptive to the local context. We present a method to find one optimal breakpoint per transform block or per multi-block partition efficiently, and we show that by using variable breakpoint, the efficiency of HVLC can be improved considerably compared to the constant breakpoint case.

Three-dimensional graphic scenes contain various mesh objects in one geometric space where different objects have potentially unequal importance regarding display. This paper proposes an object-oriented system for efficiently coding and streaming 3-D scene databases in lossy and rate-constrained environments. Vector quantization (VQ) is exploited to code 3-D scene databases into multiresolution hierarchies. For the best distortion-rate performance, adaptive quantization precisions are allocated to different objects and different layers of each object based on a weighted distortion model. Upon transmission, scalably coded objects are delivered in respective packet sequences to preserve their manipulation independency. For packet loss resilience, a plurality of FEC codes are generated as "parity objects" parallel to graphic objects, which protect the graphic objects concurrently and also preferentially in regard to their unequal decoding importance. A rate-distortion optimization framework is then developed, which performs rate allocation between graphic objects and parity objects and generates the parity data properly. We show that, by treating graphic objects jointly and preferentially in source and channel coding while preserving their independencies in transport, the proposed system reduces the receiving distortion of the 3-D database significantly compared to conventional methods.

Three-dimensional (3D) graphic scenes require considerable network bandwidth to be transmitted and computing power to be rendered on a user's terminal. Toward high-quality display in real time, we propose a sender-driven mechanism for streaming 3D scenes in a resource-constrained environment. In doing so, objects are encoded into multiresolutions to provide transmission and rendering scalability, and a weighted distortion metric is developed to measure the quality of a scene rendered with multiresolution objects, modeling objects' unequal importance regarding display. To preserve the manipulation independency of multiple objects in data delivery while provide preferential treatment for different objects as well as different layers of each object, transmission of the objects is performed over multiple streams in a partially sequenced and partially reliable fashion. A rate-distortion optimization framework is developed, which determines an optimal level of reliability for every chunk of data in each stream, taking into account the rendering importance of the object, the distortion-rate performance of the data chunks, and the statistics of the network link. Compared with heuristical methods, simulation results show that the proposed framework maximizes the display quality of the scene while minimizing the amount of data that needs to be processed by the client's rendering engine

Three-dimensional (3D) meshes are used intensively in distributed graphics applications where model data is transmitted on demand to users’ terminals and rendered for interactive manipulation. This paper presents a transmission system for such applications with an objective of minimizing the latency between the user input and the response. In particular, we represent 3D models by multiple resolutions to allow fast and scalable rendering, and provide them with unequal error protection and/or retransmission when sending the data over a lossy link. The transmission policies are determined adaptive to environment variables and in linear computation time. Simulation results show that the proposed transmission system achieves 20-30% reduction on delivering latency compared to the state-of-the-art approach in the literature.

Three-dimensional (3D) graphic scenes require considerable network bandwidth to be transmitted and computing power to be rendered on users’ terminals. Toward high-quality display in real time, we propose a sender-driven mechanism for streaming 3D scenes in a resource-constrained environment. By pre-processing the database, objects in the scene are properly weighted upon their rendering importance, and their resolutions are selected accordingly to reduce the bit rate. Partially ordered delivery is then performed using decoding independencies between the objects. Simulation results show the efficacy of the proposed mechanism. For a test benchmark, for example, the proposed algorithm outperforms the comparing heuristic by 4 dB under a 100-KB bit rate.

Three-dimensional (3D) visual scenes with pluralities of graphic objects require considerable network bandwidth to be transmitted and computing power to be rendered on a user's terminal. This paper proposes an application and transport cross-layer solution for efficiently streaming 3D scenes toward high-quality display. In so doing, 3D objects are scalably coded and are transmitted over multiple streams in a partially sequenced and partially reliable fashion. A rate-distortion optimization framework is developed to determine the optimal level of reliability for every chunk of data in each stream. Compared to heuristical methods, simulation results show that the proposed framework maximizes the display quality of the scene while minimizing the amount of data that needs to be processed by the client's rendering engine.

This paper proposes a multi-resolution coding system for 3D graphic scenes using vector quantization (VQ). For improved compression efficiency, the proposed system generates the VQ codebook for a given 3D scene using mesh objects contained in the scene database instead of separate training models. Furthermore, objects are weighted according to their unequal display importance resulting from interactions, which is incorporated into both codebook training and rate-distortion optimization. Empirical results are presented to verify the efficiency of the proposed coding system.

This paper proposes an object-oriented approach for streaming synthetic graphic contents over a packet-erasure channel. Graphic objects such as geometric meshes and texture images are coded independently into scalable resolutions and are transmitted in respective sequences to preserve their manipulation independency during packet delivery. For error resilience, FEC codes are generated as "parity objects" parallel to graphic objects. Using parity objects, multiple graphic objects are protected concurrently while also preferentially, in regard to their estimated importance on the display quality. Both the optimization framework and operational algorithm are developed for the generation of parity objects, and simulation results are presented to show the efficacy of the proposed mechanism.

Irregularly sampled triangular meshes contain vertices in a geometric space with arbitrary connectivity degrees. From a compression point of view, this letter presents a multiresolution analysis for irregular meshes using progressive vector quantization (VQ). We show that VQ exploits the joint distribution of coordinates in the geometric space, thus improving the compression efficiency. Based on the presented compression algorithm, we further propose an equalization algorithm that properly balances between connectivity downsampling and geometry quantization and achieves the optimal rate-distortion performance under constrained bit rates.

The bitstream of a progressively encoded textured model consists of multiple refinement layers. Decoding each layer produces a model with a simplified mesh and a resolution-reduced texture. We have proposed a quality measure that captures the visual fidelity of the multi-resolution textured models (Tian, D.H. and AlRegib, G., Proc. ACM Multimedia 2004, p.684-91, 2004). Based on that quality measure, we consider the problem of streaming progressively encoded textured models over a bandwidth-limited channel. We develop a bit-allocation algorithm that optimally packetizes the source bits in every transmitted data unit, such that the perceptual quality of the model displayed on the client's screen is maximized. Experimental results confirm the effectiveness of the proposed bit-allocation algorithm.

This paper addresses the problem of streaming packetized media through a proxy server to a mobile client over multiple wireless channels. We follow a rate-distortion optimized streaming approach. A real-time sender-driven streaming framework is employed at the proxy server to maximize the playback quality at the client. The experimental results show that the proposed algorithm improves the video quality by 1.3-3dB as compared to the conventional system which simply transmits the video data in the order they are displayed.

In this paper, we propose an efficient transmission method to stream textured 3D models. We develop a bit-allocation algorithm that distributes the bit budget between the geometry and the mapped texture to maximize the quality of the model displayed on the client's screen. Both the geometry and the texture are progressively and independently compressed. The resolutions for the geometry and the texture are selected to maximize the quality for a given bitrate. We further propose a novel and fast quality measure (FQM) to quantify the perceptual fidelity of the simplified model. Experimental results demonstrate the effectiveness of the proposed bit-allocation algorithm using FQM. For example, when the bit budget is 10KB, the quality of the Zebra model is improved by 15% using the proposed method compared to distributing the bit budget equally between the geometry and the texture.

In wireless video transmission, burst packet errors generally produce more catastrophic results than equal number of isolated errors. To miniimize the playback distortion it is crucial for the sender to know the packet errors at the receiver and then optimally schedule next transmissions. Unfortunately, in practice, feedback errors result in inaccurate observations of the receiving status. In this paper, we develop an optimal scheduling framework to minimize the expected distortion by first estimating the receiving status. Then, we jointly consider the source and channel characteristics and optimally choose the packets to transmit. The optimal transmission strategy is computed through a partially observable Markov decision process. The experimental results show that the proposed framework improves the average peak signal-to-noise ratio (PSNR) by 0.6-1.3 dB upon using a traditional system without packet scheduling. Moreover, we show that the proposed method smoothes out the bursty distortion periods and results in less fluctuating PSNR values.