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Detecting moving objects by using an adaptive background model is a critical component for many vision-based applications. Most background models were maintained in pixel-based forms, while some approaches began to study block-based representations which are more robust to non-stationary backgrounds. In this paper, we propose a method that combines(More)
This paper presents a new invariant local descriptor, contrast context histogram, for image matching. It represents the contrast distributions of a local region, and serves as a local distinctive descriptor of this region. Object recognition can be considered as matching salient corners with similar contrast context histograms on two or more images in our(More)
—Rough face alignments lead to suboptimal performance of face identification systems. In this study, we present a novel approach for identifying genders from facial images without proper face alignments. Instead of using only one input for test, we generate an image set by randomly cropping out a set of image patches from a neighborhood of the face(More)
We propose Binary/Appearance Tracker which consists of background subtraction, silhouette similarity and particle filter to infer pedestrians' locations under different occlusion situations with a single camera. During the period of occlu-sions, binary and color silhouettes are adaptively used to effectively measure the similarity between the observation(More)
—Shot change detection is an essential step in video content analysis. However, automatic shot change detection often suffers from high false detection rates due to camera or object movements. To solve this problem, we propose an approach based on local keypoint matching of video frames. This approach aims to detect both abrupt and gradual transitions(More)
In this paper, we propose a new invariant local descriptor, called the contrast context histogram (CCH), for image matching and object recognition. By representing the contrast distributions of a local region, it serves as a distinctive local descriptor of the region. Our experiments demonstrate that contrast-based local descriptors can represent local(More)
Keywords: Subspace methods Canonical correlation Image set Support vector machine Indefinite-kernel support vector machine Gender classification a b s t r a c t Rough face alignments result in suboptimal performance of face identification. In this study, we present an approach for identifying the gender based on facial images without proper face alignments.(More)
This study presents a computer-aided diagnosis system using sequential forward floating selection (SFFS) with support vector machine (SVM) to diagnose gastric histology of Helicobacter pylori (H. pylori) from endoscopic images. To achieve this goal, candidate image features associated with clinical symptoms are extracted from endoscopic images. With these(More)