Learn More
We present a new example-based method to colorize a gray image. As input, the user needs only to supply a reference color image which is semantically similar to the target image. We extract features from these images at the resolution of superpixels, and exploit these features to guide the colorization process. Our use of a superpixel representation speeds(More)
Depth information has been shown to affect identification of visually salient regions in images. In this paper, we investigate the role of depth in saliency detection in the presence of (i) competing saliencies due to appearance , (ii) depth-induced blur and (iii) centre-bias. Having established through experiments that depth continues to be a significant(More)
Human motion detection is a fundamental task for many computer vision tasks. The most popular method for motion detection is background subtraction where a background model needs to be maintained. In this paper an entropy based method for human motion detection is described which makes no use of background model. The difference image between consecutive(More)
In this paper, we present a new image matting algorithm that achieves state-of-the-art performance on a benchmark dataset of images. This is achieved by solving two major problems encountered by current sampling based algorithms. The first is that the range in which the foreground and background are sampled is often limited to such an extent that the true(More)
Detecting visually attentive regions of an image is a challenging but useful issue in many multimedia applications. In this paper, we describe a method to extract visual attentive regions in images using subspace estimation and analysis techniques. The image is represented in a 2D space using polar transformation of its features so that each region in the(More)
Color sampling based matting methods find the best known samples for foreground and background colors of unknown pixels. Such methods do not perform well if there is an overlap in the color distribution of foreground and background regions because color cannot distinguish between these regions and hence, the selected samples cannot reliably estimate the(More)
A novel ellipse detector based upon edge following is proposed in this paper. The detector models edge connectivity by line segments and exploits these line segments to construct a set of elliptical-arcs. Disconnected elliptical-arcs which describe the same ellipse are identified and grouped together by incrementally finding optimal pairings of(More)
Saliency detection is useful for high level applications such as adaptive compression, image retargeting, object recognition, etc. In this paper, we introduce an effective region-based solution for saliency detection. We first use the adaptive mean shift algorithm to extract superpixels from the input image, then apply Gaussian Mixture Model (GMM) to(More)
Visual attention is obtained through determination of contrasts of low level features or attention cues like intensity, color etc. We propose a new texture attention cue that is shown to be more effective for images where the salient object regions and background have similar visual characteristics. Current visual attention models do not consider local(More)