Julián Cabrera

Stochastic rate-control of video coders for wireless channels

We introduce a new approach to deal with the transmission of real-time video over wireless channels, based on a priori stochastic models for both source and channel. This new problem formulation captures in a natural way the stochastic nature of the channel as well as the uncertainty regarding the properties of the video sequence. Our formulation leads to an optimal control problem that can be solved off-line, employing standard stochastic dynamic programming techniques. The outcome of this optimization is an off-line control policy that is optimal in the sense of minimizing the average coding distortion. The on-line computational cost of the new approach is thus very low: all that is required during run-time is to identify the state of the system (source and channel). Unlike other optimization-based rate control techniques, which require a search for the optimal operating point, the operating points here for each allowable state of the system have been precalculated. We consider wireless packet-based transmission with Automatic Repeat reQuest (ARQ) error control. While a standard model has been adopted to characterize the channel behavior, a new model based on the concept of coding complexity has been devised in order to characterize the video source. Simulation results based on this new approach are provided and compared to other proposed rate-control strategies. They show how the use of model-based optimal policies has negligible on-line computational cost while providing a transmission quality comparable to that achieved with more costly deterministic dynamic programming techniques, and significantly better than for simpler algorithms that do not explicitly take into account the channel state.

Stabilization of Inverse Perspective Mapping Images based on Robust Vanishing Point Estimation

In this work, a new inverse perspective mapping (IPM) technique is proposed based on a robust estimation of the vanishing point, which provide bird-view images of the road, so that facilitating the tasks of road modeling and vehicle detection and tracking. This new approach has been design to cope with the instability that cameras mounted on a moving vehicle suffer. The estimation of the vanishing point relies on a novel and efficient feature extraction strategy, which segmentates the lane markings of the images by combining a histogram-based segmentation with temporal and frequency filtering. Then, the vanishing point of each image is stabilized by means of a temporal filtering along the estimates of previous images. In a last step, the IPM image is computed based on the stabilized vanishing point. Tests have been carried out on several long video sequences captured from cameras inside a vehicle being driven along highways and local roads, with different illumination and weather conditions, presence of shadows, occluding vehicles, and slope changes. Results have shown a significant improvement in terms of lane width constancy and parallelism between lane markings over non-stabilized IPM algorithms.

Subjective assessment of the impact of transmission errors in 3DTV compared to HDTV

Recently, broadcasted 3D video content has reached households with the first generation of 3DTV. However, few studies have been done to analyze the Quality of Experience (QoE) perceived by the end-users in this scenario. This paper studies the impact of transmission errors in 3DTV, considering that the video is delivered in side-by-side format over a conventional packet-based network. For this purpose, a novel evaluation methodology based on standard single stimulus methods and with the aim of keeping as close as possible the home environment viewing conditions has been proposed. The effects of packet losses in monoscopic and stereoscopic videos are compared from the results of subjective assessment tests. Other aspects were also measured concerning 3D content as naturalness, sense of presence and visual fatigue. The results show that although the final perceived QoE is acceptable, some errors cause important binocular rivalry, and therefore, substantial visual discomfort.

DESEO: An Active Vision System for Detection, Tracking and Recognition

In this paper, a basic conceptual architecture aimed at the design of Computer Vision System is qualitatively described. The proposed architecture addresses the design of vision systems in a modular fashion using modules with three distinct units or components: a processing network or diagnostics unit, a control unit and a communications unit. The control of the system at the modules level is designed based on a Discrete Events Model. This basic methodology has been used to design a real-time active vision system for detection, tracking and recognition of people. It is made up of three functional modules aimed at the detection, tracking, recognition of moving individuals plus a supervision module. The detection module is devoted to the detection of moving targets, using optic flow computation and relevant areas extraction. The tracking module uses an adaptive correlation technique to fixate on moving objects. The objective of this module is to pursuit the object, centering it into a relocatable focus of attention window (FOAW) to obtain a good view of the object in order to recognize it. Several focus of attention can be tracked simultaneously. The recognition module is designed in an opportunistic style in order to identify the object whenever it is possible. A demonstration system has been developed to detect, track and identify walking people.

A video-aware FEC-based unequal loss protection system for video streaming over RTP

A video-aware unequal loss protection (ULP) system for protecting RTP video streaming in bursty packet loss networks is proposed. Considering the relevance of the frame, the state of the channel, and the bitrate constraints of the protection bitstream, our algorithm selects in real time the most suitable frames to be protected through forward error protection (FEC) techniques. It benefits from a wise RTP encapsulation that allows working at a frame level without requiring any further process than that of parsing RTP headers. This makes our system straightforward and fast, perfectly suitable to be included in commercial video streaming servers. Simulation results show how our technique outperforms other proposed ULP schemes.

Quality-Control Algorithm for Adaptive Streaming Services Over Wireless Channels

Dynamic Adaptive Streaming over HTTP (DASH) is a recent MPEG standard for IP video delivery whose aim is the convergence of existing adaptive-streaming proprietary solutions. However, it does not impose any adaptation logic for selecting the quality of the media segments requested by the client, which is crucial to cope effectively with bandwidth fluctuations, notably in wireless channels. We therefore propose a solution to this control problem through Stochastic Dynamic Programming (SDP). This approach requires a probabilistic characterization of the system, as well as the definition of a cost function that the control strategy aims to minimize. This cost function is designed taking into account factors that may influence the quality perceived by the users. Unlike previous works, which compute control policies online by learning from experience, our algorithm solves the control problem offline, leading promptly to better results. In addition, we compared our algorithm to others during a streaming simulation and we analyzed the objective results by means of a Quality of Experience (QoE) oriented metric. Moreover, we conducted subjective tests to complete the evaluation of the performance of our algorithm. The results show that our proposal outperforms the other approaches in terms of both the QoE-oriented metric and the subjective evaluation.

Fast mode decision for multiview video coding based on depth maps

A new fast mode decision (FMD) algorithm for multi-view video coding (MVC) is presented. One of the multiple views is encoded based on traditional methods, which provides a mode decision (MD) map, while encoding of the other views is based on the analysis of the homogeneity of the depth map. This approach reduces the burden of the rate-distortion (RD) motion analysis based on the availability of a depth map, which is assumed to be provided by the acquisition process. Although there is a slight decrease of performance in rate-distortion terms, there is a significant reduction in computational cost.

Fast Mode Decision on H.264/AVC Main Profile Encoding Based on PSNR Predictions

In this paper we propose a new fast mode decision (FMD) algorithm to reduce the computational load of the motion estimation (ME) process of the new video coding standard H.264/AVC main profile. The algorithm firstly computes the skip/direct mode (respectively for P and B-frames), for all macroblocks (MBs), and then decides, for each MB if no mores modes are needed. This decision is based on the generation of predictions of the expected PSNR of the frame to be encoded. These predictions are performed with the distortion cost obtained for skip/direct mode jointly with the average distortion cost obtained for the previous encoded frames. Results show that the computational load have been dramatically reduced, with average encoding time saving of-36.38%, while nearly negligible loss of coding efficiency.

A new fast motion estimation and mode decision algorithm for H.264 depth maps encoding in free viewpoint TV

In this paper, we consider a scenario where 3D scenes are modeled through a View+Depth representation. This representation is to be used at the rendering side to generate synthetic views for free viewpoint video. The encoding of both type of data (view and depth) is carried out using two H.264/AVC encoders. In this scenario we address the reduction of the encoding complexity of depth data. Firstly, an analysis of the Mode Decision and Motion Estimation processes has been conducted for both view and depth sequences, in order to capture the correlation between them. Taking advantage of this correlation, we propose a fast mode decision and motion estimation algorithm for the depth encoding. Results show that the proposed algorithm reduces the computational burden with a negligible loss in terms of quality of the rendered synthetic views. Quality measurements have been conducted using the Video Quality Metric.

Low Complexity Mode Decision and Motion Estimation for H.264/AVC Based Depth Maps Encoding in Free Viewpoint Video

Within free viewpoint video, the 3-D reconstruction of the scene is created from a high number of viewpoints. Every viewpoint is represented by a traditional sequence, called texture, and its associated depth information. This is known as a View plus Depth environment. In this paper, a novel low complexity mode decision and motion estimation algorithm for the H.264/AVC based encoding of depth sequences is proposed. Given that a texture sequence and its associated depth represent the same scene from the same point of view, they should have similar motion characteristics. The complexity reduction of the depth encoding, in the proposed algorithm, is obtained by taking advantage of the texture motion information that has been previously processed by a traditional H.264/AVC encoder. The characteristics of depth and texture sequences are analyzed, focusing on similarities and differences that are properly managed to design an algorithm able to detect when the motion information of the texture might be usefully exploited in the encoding of the corresponding depth sequence. The proposed method is able to achieve the same objective quality, measured by means of the PSNR and the VQM, than a traditional H.264/AVC encoder with a reduction of up to 58% of the computational burden.