Ishani Chakraborty

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In this paper, we report a study that examines the relationship between image-based computational analyses of web pages and users' aesthetic judgments about the same image material. Web pages were iteratively decomposed into quadrants of minimum entropy (quadtree decomposition) based on low-level image statistics, to permit a characterization of these pages(More)
We consider the problem of naming objects in complex, natural scenes containing widely varying object appearance and subtly different names. Informed by cognitive research, we propose an approach based on sharing context based object hypotheses between visual and lexical spaces. To this end, we present the Visual Semantic Integration Model (VSIM) that(More)
We present a unified framework for detecting and classifying people interactions in unconstrained user generated images. Unlike previous approaches that directly map people/face locations in 2D image space into features for classification, we first estimate camera viewpoint and people positions in 3D space and then extract spatial configuration features(More)
We present a system for automated transcription of trauma resuscitation in the emergency department (ED). Using a ceiling-mounted single camera video recording, our goal is to track and transcribe the medical procedures performed during resuscitation of a patient, the time instances of their initiation and their temporal durations. In this multi-agent,(More)
In this paper we propose an algorithm for contour-based object detection in cluttered images. Contour of an object shape is approximated as a set of line segments and object detection is framed as matching contour segments of an image (i.e.,an edge image) to a boundary model of an object (i.e., a line drawing). Local shape is abstracted as a group of(More)
BACKGROUND To evaluate the usefulness and limitations of graded compression ultrasonography in the diagnosis of clinically equivocal cases of suspected acute appendicitis at the setting of mid zonal military hospital of India. METHODS A prospective study, graded compression ultrasonography with self localization was carried out with 3.5 MHz convex, 5 MHz(More)
In this paper, we propose a part-based approach to localize objects in cluttered images. We represent object parts as boundary segments and image patches. A semi-local grouping of parts named superfeatures encodes appearance and connectivity within a neighborhood. To match parts, we integrate inter-feature similarities and intra-feature connectivity via a(More)
In this paper we propose a novel method for generic object localization. The method is based on modeling the object as a graph at two levels: a local substructural representation and a global object graph. In the first level, an object substructure is a quasi affine-invariant canonical encoding of a set of four straight contour lines of the object. The(More)
The field of computer vision witnesses recently a great interest focused on solving the generic object recognition problem. Traditionally, object recognition has been at the center of the computer vision field. The explosion of digital imaging and digital video that we are witnessing makes a huge urgent demand for systems and applications that are able to(More)