IEEE Transactions on Circuits and Systems for Video Technology

We present a novel interactive image segmentation approach with user scribbles using constrained Laplacian graph optimization. A novel energy framework is developed by adding the smoothing item in the cost function of Laplacian graph energy. To the best of our knowledge, our approach is the first to incorporate the normalized cuts and graph cuts algorithms into a unified energy optimization framew... View full abstract»

Image matting refers to the problem of foreground extraction from an image and transparency determination of the pixels. Although other matting algorithms have been proposed, most are not sufficiently robust to obtain satisfactory matting results in different regions of an image, such as smooth regions, nonuniform color distribution regions and isolated color regions. This paper proposes a novel m... View full abstract»

This paper describes and provides an initial solution to a novel video editing task, i.e., video de-fencing. It targets automatic restoration of the video clips that are corrupted by fence-like occlusions during capture. Our key observation lies in the visual parallax between fences and background scenes, which is caused by the fact that the former are typically closer to the camera. Unlike in tra... View full abstract»

Tracking people and objects is a fundamental stage toward many video surveillance systems, for which various trackers have been specifically designed in the past decade. However, it comes to a consensus that there is not any specific tracker that works sufficiently well under all circumstances. Therefore, one potential solution is to deploy multiple trackers, with a tracker output fusion step to b... View full abstract»

It remains a challenging task to track an object robustly due to factors such as pose variation, illumination change, occlusion, and background clutter. In the past decades, a number of researchers have been attracted to tackling these difficulties, and they proposed many effective methods. Among them, sparse representation-based tracking method is a promising. While much success has been demonstr... View full abstract»

In this paper, we focus on optimization and enhancement of High Efficiency Video Coding (HEVC) with respect to professional applications. In most of the professional video applications, noise dominates the compression performance. We therefore theoretically and practically analyze the denoising performance of an HEVC codec and show that, especially for low to medium quantization parameters (QPs), ... View full abstract»

H.264/advanced video coding surveillance video encoders use the Skip mode specified by the standard to reduce bandwidth. They also use multiple frames as reference for motion-compensated prediction. In this paper, we propose two techniques to reduce the bandwidth and computational cost of static camera surveillance video encoders without affecting detection and recognition performance. A spatial s... View full abstract»

Smart mobile phones are capable of performing video coding and streaming over wireless networks, but are often constrained by the end-to-end delay requirement and energy supply. To achieve optimal performance under the delay and energy constraints, in this paper we extend the traditional rate-distortion (R-D) model and the previously proposed delay R-D model to a novel delay-power-rate-distortion ... View full abstract»

In this paper we consider the problem of resource allocation for video transmission over mesh networks with delay bound constraints and priority-based packet scheduling. We observe that priority-driven packet scheduling at the intermediate network routers has a direct and significant impact on the queuing behaviors and delay bound violation probabilities of video packets, as well as the overall en... View full abstract»

Boosting algorithms, especially AdaBoost, have attracted great attention in computer vision. In the early version of boosting algorithms, the weak classifier selection and the strong classifier learning are linked together. It has been demonstrated that decoupling of these two processes can provide more flexibility for training a better classifier. In these studies, linear discriminant analysis (L... View full abstract»

This paper introduces a high-speed all-hardware scale-invariant feature transform (SIFT) architecture with parallel and pipeline technology for real-time extraction of image features. The task-level parallel and pipeline structure are exploited between the hardware blocks, and the data-level parallel and pipeline architecture are exploited inside each block. Two identical random access memories ar... View full abstract»

Because of real-time requirements and low hardware-cost constraints, conventional TV scalers can only employ basic interpolation technique and thus introduces some artifacts that degrade the viewing quality of the output sequences. In this paper, a low-complexity super-resolution (SR) algorithm, which can provide vivid output image with rich details and sharp edges, and its associated hardware arc... View full abstract»

Scene text recognition has inspired great interests from the computer vision community in recent years. In this paper, we propose a novel scene text-recognition method integrating structure-guided character detection and linguistic knowledge. We use part-based tree structure to model each category of characters so as to detect and recognize characters simultaneously. Since the character models mak... View full abstract»

In this paper, we deal with the problem of video concept detection to use the concept detection results toward a more effective concept-based video retrieval. The key novelties of this paper are as follows: 1) the use of spatio-temporal video slices (tomographs) in the same way that visual keyframes are typically used in video concept detection schemes. These spatio-temporal slices capture in a co... View full abstract»