Complexity adaptation in H.264/AVC video coder for static cameras

H.264/AVC uses variable block size motion estimation (VBSME) to improve coding gain. However, its complexity is significant and fixed regardless of the required quality or of the scene characteristics. In this paper, we propose an adaptive complexity algorithm based on using the Walsh Hadamard Transform (WHT). VBS automatic partition and skip mode detection algorithms also are proposed. Experimental results show that 70% - 5% of the computation of H.264/AVC is required to achieve the same PSNR

Fast intra prediction in the transform domain

In this paper, we present a fast intra prediction method based on separating the transformed coefficients. The prediction block can be obtained from the transformed and quantized neighboring block generating minimum distortion for each DC and AC coefficients independently. Two prediction methods are proposed, one is full block search prediction (FBSP) and the other is edge based distance prediction (EBDP), that find the best matched transformed coefficients on additional neighboring blocks. Experimental results show that the use of transform coefficients greatly enhances the efficiency of intra prediction whilst keeping complexity low compared to H.264/AVC

Low computational complexity variable block size (VBS) partitioning for motion estimation using the Walsh Hadamard transform (WHT)

Variable Block Size (VBS) based motion estimation has been adapted in state of the art video coding, such as H.264/AVC, VC-1. However, a low complexity H.264/AVC encoder cannot take advantage of VBS due to its power consumption requirements. In this paper, we present a VBS partition algorithm based on a binary motion edge map without either initial motion estimation or Rate-Distortion (R-D) optimization for selecting modes. The proposed algorithm uses the Walsh Hadamard Transform (WHT) to create a binary edge map, which provides a computational complexity cost effectiveness compared to other light segmentation methods typically used to detect the required region

Using the discrete hadamard transform to detect moving objects in surveillance video

In this paper we present an approach to object detection in surveillance video based on detecting moving edges using the Hadamard transform. The proposed method is characterized by robustness to illumination changes and ghosting effects and provides high speed detection, making it particularly suitable for surveillance applications. In addition to presenting an approach to moving edge detection using the Hadamard transform, we introduce two measures to track edge history, Pixel Bit Mask Difference (PBMD) and History Update Value (H UV ) that help reduce the false detections commonly experienced by approaches based on moving edges. Experimental results show that the proposed algorithm overcomes the traditional drawbacks of frame differencing and outperforms existing edge-based approaches in terms of both detection results and computational complexity

Low complexity video compression using moving edge detection based on DCT coefficients

In this paper, we propose a new low complexity video compression method based on detecting blocks containing moving edges us- ing only DCT coe±cients. The detection, whilst being very e±cient, also allows e±cient motion estimation by constraining the search process to moving macro-blocks only. The encoders PSNR is degraded by 2dB com- pared to H.264/AVC inter for such scenarios, whilst requiring only 5% of the execution time. The computational complexity of our approach is comparable to that of the DISCOVER codec which is the state of the art low complexity distributed video coding. The proposed method ¯nds blocks with moving edge blocks and processes only selected blocks. The approach is particularly suited to surveillance type scenarios with a static camera

Automatic camera selection for activity monitoring in a multi-camera system for tennis

In professional tennis training matches, the coach needs to be able to view play from the most appropriate angle in order to monitor players' activities. In this paper, we describe and evaluate a system for automatic camera selection from a network of synchronised cameras within a tennis sporting arena. This work combines synchronised video streams from multiple cameras into a single summary video suitable for critical review by both tennis players and coaches. Using an overhead camera view, our system automatically determines the 2D tennis-court calibration resulting in a mapping that relates a player's position in the overhead camera to their position and size in another camera view in the network. This allows the system to determine the appearance of a player in each of the other cameras and thereby choose the best view for each player via a novel technique. The video summaries are evaluated in end-user studies and shown to provide an efficient means of multi-stream visualisation for tennis player activity monitoring

Low complexity intra video coding using transform domain prediction

In this paper, a new low complexity intra coding framework is presented. The proposed method is extremely computationally efficient as it uses intra prediction in the DCT domain. To facilitate finding a good predictor, we propose to extend the number of neighouring blocks to be searched, based on a consideration of the type of edges we can expect to observe in the pixel data. The best predictor can be selected from the candidate blocks without recourse to rate-distortion optimisation or pixel interpolation. To obtain better performance we also propose to automatically adapt the entropy encoding block to the prediction mode used. Experimental results show that the encoding scheme compares favorably to H.264/AVC in terms of compression efficiency but with a significant reduction in overall computational complexity

An Analytic Equation of State for Ising-like Models

Using an Environmentally Friendly Renormalization we derive, from an underlying field theory representation, a formal expression for the equation of state, $y=f(x)$, that exhibits all desired asymptotic and analyticity properties in the three limits $x\to 0$, $x\to \infty$ and $x\to -1$. The only necessary inputs are the Wilson functions $\gamma_\lambda$, $\gamma_\phi$ and $\gamma_{\phi^2}$, associated with a renormalization of the transverse vertex functions. These Wilson functions exhibit a crossover between the Wilson-Fisher fixed point and the fixed point that controls the coexistence curve. Restricting to the case N=1, we derive a one-loop equation of state for $2< d<4$ naturally parameterized by a ratio of non-linear scaling fields. For $d=3$ we show that a non-parameterized analytic form can be deduced. Various asymptotic amplitudes are calculated directly from the equation of state in all three asymptotic limits of interest and comparison made with known results. By positing a scaling form for the equation of state inspired by the one-loop result, but adjusted to fit the known values of the critical exponents, we obtain better agreement with known asymptotic amplitudes.Comment: 10 pages, 2 figure

Sampling low-fidelity outputs for estimation of high-fidelity density and its tails

In a multifidelity setting, data are available under the same conditions from two (or more) sources, e.g. computer codes, one being lower-fidelity but computationally cheaper, and the other higher-fidelity and more expensive. This work studies for which low-fidelity outputs, one should obtain high-fidelity outputs, if the goal is to estimate the probability density function of the latter, especially when it comes to the distribution tails and extremes. It is suggested to approach this problem from the perspective of the importance sampling of low-fidelity outputs according to some proposal distribution, combined with special considerations for the distribution tails based on extreme value theory. The notion of an optimal proposal distribution is introduced and investigated, in both theory and simulations. The approach is motivated and illustrated with an application to estimate the probability density function of record extremes of ship motions, obtained through two computer codes of different fidelities.Comment: 32 pages, 11 figures, 2 table