Change detection by background subtraction is a common approach to detect moving foreground. The resulting difference image is usually thresholded to obtain objects based on pixel connectedness and resulting blob objects are subsequently tracked. This paper proposes a detection approach not requiring the binarization of the difference image. Local density maxima in the difference image usually ...

Motivated by the significant overdensity of background bright quasars recently detected behind the foreground clusters of galaxies on scale of 10 arcminutes, we have investigated the possibility of attributing the quasar-cluster associations to gravitational lensing by large-scale matter inhomogeneities. Based on the conventional lensing models, we have shown that the reported quasar overdensit...

This paper presents a compressed-domain fall incident detection scheme for intelligent homecare applications. For object extraction, global motion parameters are estimated to distinguish local object motions from camera motions so as to obtain a rough object mask. We then perform change detection and/or background subtraction on the DC+2AC images extracted from the incoming coded bitstream to r...

Rapid advances in DNA sequencing improve existing techniques and enable new approaches in genetics and functional genomics, bringing about unprecedented coverage, resolution and sensitivity. Enhanced toolsets can facilitate the untangling of connections between genomic variation, environmental factors and phenotypic effects, providing novel opportunities, but may also pose challenges in data in...

This work presents a new robust PCA method for foreground-background separation on freely moving camera video with possible dense and sparse corruptions. Our proposed method registers the frames of the corrupted video and then encodes the varying perspective arising from camera motion as missing data in a global model. This formulation allows our algorithm to produce a panoramic background comp...

This paper presents a technique for motion detection that incorporates several innovative mechanisms. our proposed technique stores, a set of values taken in the past at the same location or in the neighborhood of each pixel. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which va...

This paper presents an online learning algorithm for appearancebased gaze estimation that allows free head movement in a casual desktop environment. Our method avoids the lengthy calibration stage using an incremental learning approach. Our system keeps running as a background process on the desktop PC and continuously updates the estimation parameters by taking user’s operations on the PC moni...