Jo Yew Tham

Cost effective IP camera for video surveillance

IP cameras are key devices for a video surveillance system. This paper introduces a cost effective, power efficient and low profile IP Camera. The camera consists of a video preprocessing unit, an H.264 encoder, and an embedded streaming server. The video preprocessing unit is used for video data acquisition and format conversion; the H.264 encoder compresses the preprocessed data with H.264 baseline encoding tools; and the streaming server produces a continuous flow of data for the Internet video communication and surveillance applications. Both the encoder and the streaming server are implemented with the cost effective and power efficient Blackfin DSP and ARM9 processors. Key approaches for efficient usage of the DSP resources and main optimization methods for the encoding speed are presented in this paper. Performance tests and practical uses of the IP camera indicate that it is easy to use and able to deliver CIF or VGA size of real-time video clips directly to the Internet with high PSNR quality and low bitrates. Application of these IP cameras to the video surveillance systems may greatly lower the requirements for the network bandwidth, significantly improve the video quality, and efficiently enhance the system reliability accordingly.

Complexity Scalable H.264/AVC Encoding

The H.264/AVC video coding standard encapsulates the most advanced video coding tools. Since the various techniques that lead to better coding efficiency of the coding standard also inevitably increase the complexity of the video encoder, real-time H.264 encoding of video streams is a challenging task. If available computational resource does not allow the entire encoding process to be carried out in time, a complexity scalable technique that ensures a graceful degradation of coding performance will be a valuable tool. We designed a video encoding scheme that allows the rate distortion (R-D) process to be carried out in a complexity scalable fashion. Our proposed singularly parameterized complexity scalable scheme allows the control of complexity-coding performance tradeoff when available resources are limited and the optimal R-D performance is unattainable.

Complexity scalable rate-distortion optimization for H.264/AVC

The H.264/AVC video coding standard encapsulates the most advanced video coding tools. The various techniques that lead to better coding efficiency of the coding standard also inevitably increase the complexity of the video encoder. Thus, real-time encoding of video streams with H.264 coding standard is a challenging task. If available computational resource does not allow the entire encoding process to be carried out in time, a complexity scalable technique that ensures a graceful degradation of coding performance will be a useful tool. This work proposes a singularly-parameterized complexity scalable rate-distortion framework for H.264/AVC encoders.

Complexity-Rate-Distortion Optimization for Real-Time H.264/AVC Encoding

In this paper, we introduce a singularly-parameterized complexity scalable H.264-compliant encoder. Through modeling its complexity-rate-distortion relationships, we derive optimized operating mode of the encoder (rate and complexity) and show through experiment that such optimization can help a video encoder operate within rate and time constraints. The design of the complexity scalable encoding scheme enables the encoder to perform optimization while taking into consideration the availability of computational resource. This extension of traditional rate-distortion optimization is necessary when time or power constraints do not allow a video encoder to achieve rate-distortion optimized coding performance. Our optimization scheme outputs parameters that allow the encoder to be as close to being rate-distortion optimized as possible, within rate and complexity constraints. Index Terms—H.264, power consumption, complexity

A novel scheme of generating streamable MP4 files for scalable video coding

In this paper, we present an innovative scheme that efficiently creates SVC-MP4 files from raw video files, and hint them into streamable files. Unlike hinting schemes in the literature, where extractors and aggregators are heavily relied, no extractors or aggregators are required. In proposed system, SVC layers are presented as separate media tracks and the hint tracks are generated from the corresponding media tracks. The resulting MP4 files strictly comply with the ISO/IEC 14496-14 standards and applicable to streaming servers. The paper provides guideline and paradigm for research and development on streaming technologies for SVC media.

An optimal smooth QoS adaptation strategy for QoS differentiated scalable media streaming

Due to the advance of technologies in multimedia compression and network communications, scalable media streaming services have been availed to provide QoS differentiated services for heterogeneous users. However, it is still a big challenge to support consistent end-to-end quality of services (QoS) for the users due to the dynamic feature of the Internet, and abrupt variability of the network resources may severally affect the client perceived QoS. In this paper, we address the issues of smooth QoS adaptation for scalable streaming services. We propose an Optimal Smooth QoS Adaptation (OS-QA) strategy which allocates the server resource adaptively to cope with the variability of network bandwidth and protects the service quality of different quality classes under dynamic resource constraints. We analyze the quality variation caused by resource fluctuation and proposed OS-QA to minimize the average QoS variance under the resource constraints. Simulations are conducted to compare our proposed method with other QoS adaptation methods, and performance is analyzed in terms of QoS variance and PSNR. Results show that our proposed method is able to gracefully adapt the QoS and protect the client perceived QoS by minimizing the QoS variance under dynamic network resource constrains.

An Adaptive Thresholding Technique for the Detection of All-Zeros Blocks in H. 264

In H.264 video coding, there are a substantial number of 4x4 blocks becoming all-zeros after transformation and quantization. This is a waste of computational resources because these skipped blocks do not require forward transform and quantization. We proposed a very effective early detection of fast skipped block detections based on the theoretical derivation of H.264 integer transform and quantization. The experimental results show that the algorithm can detect 9.71%-43.35% more zero blocks than Yongs method.

Pattern selection for error-resilient slice interleaving based on receiver error concealment technique

Video communication is often afflicted by packet loss over unreliable networks. To alleviate the quality degradation in the situation of packet loss, this paper proposes a novel error resilient slice interleaving method for compressed video packetization. Each packet is constructed by interleaving independently decodable slices of the coded video bit-stream in consecutive frames. The optimal interleaving pattern for minimizing the overall distortion of the decoded video, subject to a delay constraint, is determined based on the error concealment technique employed at the user end. Compared with traditional error-resilient methods, this scheme greatly improves the overall performance without requiring an increase in bit-rate. Experimental results on different video sequences demonstrate the effectiveness of the proposed approach.

Edge Weighted Spatio-Temporal Search for Error Concealment

In temporal error concealment (EC), the sum of absolute difference (SAD) is commonly used to identify the best replacement macroblock. Even though the use of SAD ensures spatial continuity and produces visually good results, it is insufficient to ensure edge alignment. Other distortion criteria based solely on structural alignment may also perform poorly in the absence of strong edges. In this paper, we propose a spatio-temporal EC search algorithm using an edge weighted SAD distortion criterion. This distortion criterion ensures both edge alignment and spatial continuity. We assume the loss of motion information and use zero motion vector as the starting search point. We show that the proposed algorithm outperforms the use of unweighted SAD in general. Most importantly, the perceptual quality of EC is improved due to edge alignment while ensuring spatial continuity.

Efficient rate-quantization model for frame level rate control in spatially scalable video coding

This paper addresses the quantization parameter (QP) selection problem in H.264 spatially scalable video coding (SVC). For frame level rate control in SVC, it is important to have an accurate QP selection scheme such that the target bit rate of each coding layer will be achieved. In this paper, we present an adaptive rate-quantization (R-Q) model to select the appropriate QP for each inter frame in spatial enhancement layers according to the target bit rate. The proposed algorithm introduces an efficient coding complexity estimation method by taking into consideration the inter-layer dependency between different spatial layers. Based on the coding complexity information, the R-Q model parameters can be adaptively updated. Experimental results demonstrate that compared to the traditional method, the proposed method provides better estimation accuracy for bit rate in terms of target bits mismatch error and thus it is very desirable for H.264/SVC rate control applications.