Jianbing Shen

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We introduce an unsupervised, geodesic distance based, salient video object segmentation method. Unlike traditional methods, our method incorporates saliency as prior for object via the computation of robust geodesic measurement. We consider two discriminative visual features: spatial edges and temporal motion boundaries as indicators of foreground object(More)
This paper presents a novel gradient-based image completion algorithm for removing significant objects from natural images or photographs. Our method reconstructs the region of removal in two phases. Firstly, the gradient maps in the removed area are completed through a patch based filling algorithm. After that, the image is reconstructed from the gradient(More)
We present a novel spatiotemporal saliency detection method to estimate salient regions in videos based on the gradient flow field and energy optimization. The proposed gradient flow field incorporates two distinctive features: 1) intra-frame boundary information and 2) inter-frame motion information together for indicating the salient regions. Based on the(More)
We present a novel image superpixel segmentation approach using the proposed lazy random walk (LRW) algorithm in this paper. Our method begins with initializing the seed positions and runs the LRW algorithm on the input image to obtain the probabilities of each pixel. Then, the boundaries of initial superpixels are obtained according to the probabilities(More)
Existing real-time automatic video abstraction systems rely on local contrast only for identifying perceptually important information and abstract imagery by reducing contrast in low-contrast regions while artificially increasing contrast in higher contrast regions. These methods, however, may fail to accentuate an object against its background for the(More)
A novel sub-Markov random walk (subRW) algorithm with label prior is proposed for seeded image segmentation, which can be interpreted as a traditional random walker on a graph with added auxiliary nodes. Under this explanation, we unify the proposed subRW and other popular random walk (RW) algorithms. This unifying view will make it possible for(More)
In this paper, we present a novel high-quality intrinsic image recovery approach using optimization and user scribbles. Our approach is based on the assumption of color characteristics in a local window in natural images. Our method adopts a premise that neighboring pixels in a local window having similar intensity values should have similar reflectance(More)
In this paper, we present a novel detail-preserving fusion approach from multiple exposure images using subband architecture. Given a sequence of different exposures, the Quadrature Mirror Filter (QMF) based subband architecture is first employed to decompose the original sequence into different frequency subbands. After that, we compute the importance(More)
This paper presents a novel feature-aware rendering system that automatically abstracts videos and images with the goal of improving the effectiveness of imagery for visual communication tasks. We integrate the bilateral grid to simplify regions of low contrast, which is faster than the separable approximation to the bilateral filter, and use a feature(More)