Adaptive Rate Control Algorithm for H.264/AVC Considering Scene Change

Chen, Xiao; Lü, Feifei

doi:10.1155/2013/373689

Cited by 4 publications

(6 citation statements)

References 31 publications

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“…Chen et al [23] proposed a new approach for scene detection from the H.264 video sequences. They define a scene change factor which is used to reserve bits for each frame.…”

Section: Scene Detectionmentioning

confidence: 99%

Video Scene Detection Using Compact Bag of Visual Word Models

Haroon

Baber

Ullah

et al. 2018

Advances in Multimedia

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Video segmentation into shots is the first step for video indexing and searching. Videos shots are mostly very small in duration and do not give meaningful insight of the visual contents. However, grouping of shots based on similar visual contents gives a better understanding of the video scene; grouping of similar shots is known as scene boundary detection or video segmentation into scenes. In this paper, we propose a model for video segmentation into visual scenes using bag of visual word (BoVW) model. Initially, the video is divided into the shots which are later represented by a set of key frames. Key frames are further represented by BoVW feature vectors which are quite short and compact compared to classical BoVW model implementations. Two variations of BoVW model are used: (1) classical BoVW model and (2) Vector of Linearly Aggregated Descriptors (VLAD) which is an extension of classical BoVW model. The similarity of the shots is computed by the distances between their key frames feature vectors within the sliding window of length L, rather comparing each shot with very long lists of shots which has been previously practiced, and the value of L is 4. Experiments on cinematic and drama videos show the effectiveness of our proposed framework. The BoVW is 25000-dimensional vector and VLAD is only 2048-dimensional vector in the proposed model. The BoVW achieves 0.90 segmentation accuracy, whereas VLAD achieves 0.83.

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“…Chen et al [23] proposed a new approach for scene detection from the H.264 video sequences. They define a scene change factor which is used to reserve bits for each frame.…”

Section: Scene Detectionmentioning

confidence: 99%

Video Scene Detection Using Compact Bag of Visual Word Models

Haroon

Baber

Ullah

et al. 2018

Advances in Multimedia

View full text Add to dashboard Cite

show abstract

“…They also classified the complexity of sequences into three levels to respectively assign various QP values. Recently, Chen and Liu applied a scene change factor (SCF) to estimate the frame complexity, and the target bits estimation was classified into five levels based on the SCF value [12] In this work, some experiments were designed to illustrate the influence of a scene change to the H.264/AVC performance. The proposed method was to reinforce this unaddressed part of H.264/AVC, and was performed by two steps.…”

Section: Copyright C 200x the Institute Of Electronics Information Amentioning

confidence: 99%

“…Furthermore, to maintain the stability of the video, the maximal difference of the QP value between two consecutive frames is restricted to 2. The related work on the rate control algorithms is covered in [8]- [12].…”

Section: Review Of Rate Control Algorithms Of H264/avcmentioning

confidence: 99%

“…where H and V are the horizontal and vertical sizes of the frame, respectively, and I i, j is the luminance value of the pixel at location (i, j) [14]. Similar to the quadratic ratedistortion model [4], (12) also connects the target bits; QP, which the quantization step size expresses; and frame complexity, which the average gradient per pixel estimates. The target bits can be equally distributed to each frame, because (12) is only applicable to all I-frame sequences.…”

Section: Qp Initialization For An Ordinary Gopmentioning

confidence: 99%

“…Several methods have been proposed for modifying JM, the reference software of H.264/AVC, to improve the rate control performance as a scene change is detected. An effective method is to create a transition GOP for the scenechanged frame and the remaining frames in the original GOP [9], [12]. This method works because the content of the scene-changed frame is dissimilar from the contents of its previous frames, and thus most of the blocks in the scenechanged frame are encoded using intra-coding.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Rate Control Mechanism in H.264/AVC for Scene Changes

Fang

Chen

Chan

et al. 2014

IEICE Trans. Fundamentals

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Rate control that is required to regulate the bitrate of video coding is critical to time-sensitive video applications used over networks. However, the H.264/AVC standard does not respond to scene changes, and this causes the transmission quality to deteriorate as a scene change occurs. In this work, a scene change is detected by comparing the ratio of the sum of absolute difference (SAD) between two consecutive frames. As the scene change is detected, the proposed method, which is modified from the reference software of H.264/AVC, reassigns a quantization parameter (QP) value to regulate the bitrate. Because the inter-prediction works poorly for the scene-changed frame, the proposed method estimates its frame complexity based on the content, and further creates another Q-R model to assign QP. The adaptive rate control mechanism presented in this study can quickly respond to the heavy bitrate increment caused by a change of scene. Simulation results show that the proposed method improves the average peak signal noise ratio (PSNR) to approximately 1.1 dB, with a smaller buffer size compared with the performance of the reference software JM version 17.2.

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