Human action recognition in videos is a challenging problem with wide applications. State-of-the-art approaches often adopt the popular bag-of-features representation based on isolated local patches or temporal patch trajectories, where motion patterns like object relationships are mostly discarded. This paper proposes a simple representation specifically aimed at the modeling of such motion re...

Image matting is the process of taking an image, isolating the foreground, and replacing the background with a new image. This can be a hard problem when the background is unknown as it is fundamentally unconstrained. We look at an existing technique for foreground-background separation called Bayesian matting and improve upon it by adding depth information acquired by a time-of-flight range sc...

Human activity recognition is an important research area of computer vision which dictates the need to automatically detect and retrieve semantic events in videos based on video contents. In this paper, we attempt to extract the foreground object from the video clip using color model and generate a unique signal pattern for the detected foreground (human). Signal pattern is generated for the ex...

Camouflage is an attempt to conceal the signature of a target object into the background image. Camouflage detection methods or Decamouflaging method is basically used to detect foreground object hidden in the background image. In this research paper authors presented survey of camouflage detection methods for different applications and areas. © 2012 The Authors. Published by Elsevier B.V. Sele...

Statistical observations of the Epoch of Reionization using the 21 cm line of neutral hydrogen have the potential to revolutionize our understanding of structure formation and the first luminous objects. However, these observations are complicated by a host of strong foreground sources. Several foreground removal techniques have been proposed in the literature, and it has been assumed that thes...

Background subtraction is a fundamental video analysis technique that consists of creation of a background model that allows distinguishing foreground pixels. We present a new method in which the image sequence is assumed to be made up of the sum of a low-rank background matrix and a dynamic tree-structured sparse matrix. The decomposition task is then solved using our approximated Robust Princ...

Automatic discovery of foreground objects in video sequences is important in computer vision, with applications to object tracking, video segmentation and weakly supervised learning. This task is related to cosegmentation [4, 5] and weakly supervised localization [2, 6]. We propose an efficient method for the simultaneous discovery of foreground objects in video and their segmentation masks acr...