Catálogo de publicaciones - libros

The emerging H.264/AVC video coding standard improves coding performance significantly by adopting many advanced techniques. This is achieved at the expense of great increase of encoder complexity. Specifically, the intra prediction using RDO examines all possible combinations of coding modes, which depend on spatial directional correlation with adjacent blocks. There are 9 modes for a 4×4 luma block, and 4 modes for a 16×16 luma block and an 8×8 chroma block, respectively. Therefore the number of mode combinations for each MB is 592. This paper proposes a complexity reduction algorithm using simple directional masks and neighboring modes. The proposed method reduces the number of mode combinations into 132 at the most. Simulation results show the proposed method reduces the encoding time up to 70% with negligible loss of PSNR and bit-rate increase compared with the H.264/AVC exhaustive search.

We propose a detection method of corner outlier artifacts and a simple and effective filter in order to remove the artifacts in highly compressed video. We detect the corner outlier artifacts based on the direction of edges going through a block corner and the properties of blocks around the edges. Based on the detection results, we remove the stair-shaped discontinuities, i.e., corner outlier artifacts, using the neighboring pixels of the corner outlier artifact in the spatial domain. Simulation results show that the proposed method improves, particularly in combination with a deblocking filter, both objective performance and subjective visual quality.

In this paper, we present a sports analysis system, which not only recognizes the semantic events, but also concludes the behavior, like player’s tactics. To this end, we propose an advanced multiple-player tracking algorithm, which addresses two improvements on practical problems: (1) updating of the player template so that it remains a good model over time, and (2) adaptive scaling of the template size depending on the player motion. In this algorithm, we obtain the initial locations of players in the first frame. The tracking is performed by considering both the kinematic constraints of the player and the color distribution of appearance, thereby achieving promising results. We demonstrate the performance of the proposed system by evaluating it for double tennis matches where the player count and the resulting occlusions are challenging.

Because of limitation of low power and computational ability in mobile video devices, it is significant to develop energy-efficient wireless video compression methods for mobile video systems. In this paper, a new approach to low complexity wireless video compression is proposed, based on Wyner-Ziv coding theorem. The proposed method encodes video only by intracoding techniques and detection of regions of interest, without the complicated motion estimation and compensation in the mobile video terminal. Thus, the computational burden is obviously reduced and the requirement of low power can be satisfied in mobile video devices. Experimental results show that the proposed method is quite effective.

Disparity estimation can be used to eliminate redundancy among different views in multi-view video compression to obtain high compression efficiency. However, the problem of high computational complexity in disparity estimation, which limits real-time applications of multi-view systems, needs to be solved. In this paper, a novel fast multi-view disparity estimation algorithm based on Hadamard similarity coefficient for multi-view video coding is proposed by using prediction of initial search point, selection of reference view, determination of the best disparity vector, and strategies of search stop. Experimental results show that the proposed algorithm can significantly reduce the computational complexity in multi-view disparity estimation.

In this paper, we present AddCanny, an Anisotropic Diffusion and Dynamic reformulation of the Canny edge detector. The proposal provides two modifications to classical Canny detector. The first one consists of using an anisotropic diffusion filter instead of a Gaussian filter as Canny does in order to obtain better edge detection and location. The second one is the replacement of the hysteresis step by a dynamic threshold process, in order to reduce blinking effect of edges during successive frames and, therefore, generate more stable edges in sequences. Also, a new performance measurement based on the Euclidean Distance Transform to evaluate the consistency of computed edges is proposed. The paper includes experimental evaluations with different video streams that illustrate the advantages of AddCanny compared to classical Canny edge detector.

Facial expression hallucination is an important approach to facial expression synthesis. Existing works mainly focused on synthesizing a static facial expression image given one face image with neutral expression. In this paper, we propose a novel two-level hierarchical fusion approach to hallucinate dynamic expression video sequences when given only one neutral expression face image. By fusion of local linear and global nonlinear subspace learning, the two-level approach provides a sound solution to organizing the complex video sample space. Experiments show that our approach generates reasonable facial expression sequences both in temporal domain and spatial domain with less artifact compared with existing works.

Content analysis of video and still images is attractive for multiple reasons, such as enabling content-based actions and image manipulation. This paper presents a new algorithm and feature model for blue-sky detection. The algorithm classifies the sky areas by computing a pixel-accurate sky probability. Such a probabilistic measure matches well with the requirements of typical video enhancement functions in TVs. This algorithm enables not only content-adaptive picture quality improvement, but also more advanced applications such as content-based annotation of, and retrieval from image and video databases. When compared to existing algorithms, our proposal shows considerable improvements in correct detection/rejection rate of sky areas, and an improved consistency of the segmentation results.

In the context of Universal Multimedia Access, efficient techniques are needed for the adaptation of video content. An important example is the reduction of the bitrate in order to satisfy the bandwidth constraints imposed by the network or the decoding capability of the terminal devices. Requantization transcoding is a fast technique for bitrate reduction, and has been successfully applied in previous video coding standards such as MPEG-2. In this paper, we examine requantization in H.264/AVC, focusing on the intra 16×16 prediction modes. Due to the newly introduced coding tools in H.264/AVC, new techniques are needed that are able to lower the bitrate at a minimal quality loss. We propose two novel architectures, one in the pixel domain and one in the frequency domain, that reuse the information from the incoming bitstream in an efficient way, and perform approximately equally well as a cascade of decoder and encoder. Due to their low computational complexity, the introduced architectures are highly suitable for on-the-fly video adaptation scenarios.

In this paper, we propose a new deinterlacing method using motion estimation and compensation of edge regions. Although motion-compensated deinterlacing methods provide significant results in interlaced-to-progressive conversion, they still have undesirable artifacts in fast moving areas and edge regions. The proposed method mitigates the problems by applying the edge region motion estimation and compensation with properly small search range. After filling the missing lines with the conventional spatial and temporal methods, motion estimation and compensation is applied to the predefined edge areas. Experimental results show that the proposed method produces noticeable improvement more than existing motion-compensated deinterlacing methods.