Region-of-interest (ROI) detection plays an important role in filtering out pornographic images. Skin-color models, as a traditional approach, extract skin-color regions as ROI. However, the approach is difficult to differentiate between human skins and other objects with the skin-color. Furthermore, skin-color regions are always larger than the subareas containing pornographic parts. In this p...

A standard approach to learning object category detectors is to provide strong supervision in the form of a region of interest (ROI) specifying each instance of the object in the training images [17]. In this work are goal is to learn from heterogeneous labels, in which some images are only weakly supervised, specifying only the presence or absence of the object or a weak indication of object l...

In this paper algorithm to detects human facial features like the mouth, nose and eyes in a full frontal face image is proposed. The new algorithm is proposed in order to detect automatically face features (eyes, mouth and nose) and extract their corresponding geometrical point. This project presents and implements a facial feature point extraction and recognition method of facial expression an...

Breast skin–air interface and pectoral muscle segmentation are usually first steps in all CAD applications on scanned as well as digital mammograms. Breast skin–air interface segmentation is much more difficult task when performed on scanned mammograms than on digital mammograms. In case of pectoral muscle segmentation, segmentation difficulty of analog and digital mammograms is usually similar...

In this work, we tackle the problem of instance segmentation, the task of simultaneously solving object detection and semantic segmentation. Towards this goal, we present a model, called MaskLab, which produces three outputs: box detection, semantic segmentation, and direction prediction. Building on top of the Faster-RCNN object detector, the predicted boxes provide accurate localization of ob...

When reviewing collections of video such as recorded meetings or presentations, users are often interested only in an overview or short segments of these documents. We present techniques that use automatic feature analysis, such as slide detection and applause detection, to help locate the desired video and to navigate to regions of interest within it. We built a web-based interface that graphi...

We present a new, sophisticated algorithm to select suitable training images for our biologically motivated attention system VOCUS. The system detects regions of interest depending on bottom-up (scenedependent) and top-down (target-specific) cues. The top-down cues are learned by VOCUS from one or several training images. We show that our algorithm chooses a subset of the training set that outp...

This paper describes the extraction of information from polarimetric tomographic SAR data. This analysis is performed in three steps. Polarimetric tomographic data are first processed using a Capon-based vectorial spectral analysis technique, in order to extract physical and geometrical information over vertical structures. Then, a feature detection procedure with automatic scale selection is a...

In this paper we have proposed a Computer Aided Detection (CAD) scheme for the early detection of Ischemic Stroke using Adaptive Region of interest. A number of statistical parameters such as Energy and Entropy will be calculated from the Adaptive Region of interest and these will be compared with the contra-lateral side of the brain. Keywords— Ischemic stroke, Computer aided detection, Adaptiv...