Rangachar Kasturi

University of South Florida | USF · Department of Computer Science & Engineering

This paper presents the first multimodal neonatal pain dataset that contains visual, vocal, and physiological responses following clinically required procedural and postoperative painful procedures. It was collected from 58 neonates (27-41 gestational age) during their hospitalization in the neonatal intensive care unit. The visual and vocal data w...

The current practice for assessing neonatal postoperative pain relies on bedside caregivers. This practice is subjective, inconsistent, slow, and discontinuous. To develop a reliable medical interpretation, several automated approaches have been proposed to enhance the current practice. These approaches are unimodal and focus mainly on assessing ne...

The current practice for assessing neonatal postoperative pain relies on bedside caregivers. This practice is subjective, inconsistent, slow, and discontinuous. To develop a reliable medical interpretation, several automated approaches have been proposed to enhance the current practice. These approaches are unimodal and focus mainly on assessing ne...

This paper presents the first investigation into the use of fully automated deep learning framework for assessing neonatal postoperative pain. It specifically investigates the use of Bilinear Convolutional Neural Network (B-CNN) to extract facial features during different levels of postoperative pain followed by modeling the temporal pattern using...

Neonatal pain assessment in clinical environments is challenging as it is discontinuous and biased. Facial/body occlusion can occur in such settings due to clinical condition, developmental delays, prone position, or other external factors. In such cases, crying sound can be used to effectively assess neonatal pain. In this paper, we investigate th...

Neonates do not have the ability to either articulate pain or communicate it non-verbally by pointing. The current clinical standard for assessing neonatal pain is intermittent and highly subjective. This discontinuity and subjectivity can lead to inconsistent assessment, and therefore, inadequate treatment. In this paper, we propose a multi-channe...

Infants receiving care in the Neonatal Intensive Care Unit (NICU) experience several painful procedures during their hospitalization. Assessing neonatal pain is difficult because the current standard for assessment is subjective, inconsistent, and discontinuous. The intermittent and inconsistent assessment can induce poor treatment and, therefore,...

The current standard for assessing neonatal pain is discontinuous and inconsistent because it depends highly on the observers bias. These drawbacks can result in delayed intervention and inconsistent treatment of pain. Convolutional Neural Networks (CNNs) have gained much popularity in the last decades due to the wide range of its successful applic...

Infants receiving care in the Neonatal Intensive Care Unit (NICU) experience several painful procedures during their hospitalization. Assessing neonatal pain is difficult because the current standard for assessment is subjective, inconsistent, and discontinuous. The intermittent and inconsistent assessment can induce poor treatment and, therefore,...

Neonates needs an intensive health care during their early life. The cost of health care is high. In addition, health care might not be accessible to neonates in rural areas. In this paper, we propose the development of a smart, accessible, and cost-effective system to monitor neonates' health conditions using the advanced technologies of artificia...

We address the problem of suppressing facial expressions in videos because expressions can hinder the retrieval of important information in applications such as face recognition. To achieve this, we present an optical strain suppression method that removes any facial expression without requiring training for a specific expression. For each frame in...

Transfer learning using pre-trained Convolutional Neural Networks (CNNs) has been successfully applied to images for different classification tasks. In this paper, we propose a new pipeline for pain expression recognition in neonates using transfer learning. Specifically, we propose to exploit a pre-trained CNN that was originally trained on a rela...

Bedside caregivers assess infants' pain at constant intervals by observing specific behavioral and physiological signs of pain. This standard has two main limitations. The first limitation is the intermittent assessment of pain, which might lead to missing pain when the infants are left unattended. Second, it is inconsistent since it depends on the...

The current practice of assessing infants’ pain is subjective and intermittent. The misinterpretation or lack of attention to infants’ pain experience may lead to misdiagnosis and over- or under-treatment. Studies have found that poor management and treatment of infants’ pain can cause permanent alterations to the brain structure and function. To a...

In autonomous driving applications a critical challenge is to identify the action to take to avoid an obstacle on a collision course. For example, when a heavy object is suddenly encountered it is critical to stop the vehicle or change the lane even if it causes other traffic disruptions. However, there are situations when it is preferable to colli...

The objective of this work is to estimate 3D human pose from a single RGB image. Extracting image representations which incorporate both spatial relation of body parts and their relative depth plays an essential role in accurate3D pose reconstruction. In this paper, for the first time, we show that camera viewpoint in combination to 2D joint locati...

The objective of this work is to estimate 3D human pose from a single RGB image. Extracting image representations which incorporate both spatial relation of body parts and their relative depth plays an essential role in accurate3D pose reconstruction. In this paper, for the first time, we show that camera viewpoint in combination to 2D joint lo-cat...

In autonomous driving applications a critical challenge is to identify action to take to avoid an obstacle on collision course. For example, when a heavy object is suddenly encountered it is critical to stop the vehicle or change the lane even if it causes other traffic disruptions. However,there are situations when it is preferable to collide with...

The current practice of assessing infants' pain depends on using subjective tools that fail to meet rigorous psychometric standards and requires continuous monitoring by health professionals. Therefore, pain may be misinterpreted or totally missed leading to misdiagnosis and over/under treatment. To address these shortcomings, the current practice...

Mislabeled examples in the training data can severely affect the performance of supervised classifiers. In this paper, we present an approach to remove any mislabeled examples in the dataset by selecting suspicious examples as targets for inspection. We show that the large margin and soft margin principles used in support vector machines (SVM) have...

We report novel results of utilizing infant facial tissue distortion as a pain indicator in video-sequences of ten infants based on analysis of facial strain. Facial strain, which is used as the main feature for classification, is generated for each facial expression and then used to train two classifiers, k Nearest-Neighbors (KNN) and support vect...

Person recognition has been a challenging research problem for computer vision researchers for many years. A variation of this generic problem is that of identifying the reappearance of the same person in different segments to tag people in a family video. Often we are asked to answer seemingly simple queries such as ‘how many different people are...

We propose a novel method by using three new character features to detect text objects comprising two or more isolated characters in images and videos. A new text model is constructed to describe text objects. Each character is a part in the model and every two neighboring characters are connected by a link. Two characters and the link connecting t...

Sign text is one of the most seen text types appearing in scene images. In this paper, we present a new sign text localization method for scene images captured by mobile device. The candidate characters are first localized by detecting closed boundaries in the image. Then, based on the properties of signboard, the convex regions that contain enough...

The problem of detection of label-noise in large datasets is investigated. We consider applications where data are susceptible to label error and a human expert is available to verify a limited number of such labels in order to cleanse the data. We show the support vectors of a Support Vector Machine (SVM) contain almost all of these noisy labels....

The aim of this study is to investigate a data mining approach to help assess consequences of oil spills in the maritime environment. The approach under investigation is based on detecting suspected oil droplets in the water column adjacent to the Deepwater Horizon oil spill. Our method automatically detects particles in the water, classifies them...

Extracting text objects from scene images is a challenging problem. In this paper, by investigating the properties of single characters and text objects, we propose a new text extraction approach for scene images. First, character energy is computed based on the similarity of stroke edges to detect candidate character regions, then link energy is c...

A novel wire detection algorithm for use by unmanned aerial vehicles (UAV) in low altitude urban reconnaissance is presented. This is of interest to urban search and rescue and military reconnaissance operations. Detection of wires plays an important role, because thin wires are hard to discern by tele-operators and automated systems. Our algorithm...

Shape analysis is an active and important branch in computer vision research field. In recent years, many geometrical, topological, and statistical features have been proposed and widely used for shape-related applications. In this paper, based on the properties of Distance Transform, we present a new shape feature, weight of boundary point. By com...

A novel thin line detection algorithm for use in low-altitude aerial vehicles is presented. This algorithm is able to detect thin obstacles such as cables, power lines, and wires. The system is intended to be used during urban search and rescue operations, capable of dealing with low-quality images, robust to image clutter, bad weather, and sensor...

This paper describes a vision-based street detection algorithm to be used by small autonomous aircraft in low-altitude urban surveillance. The algorithm uses Bayesian analysis to differentiate between street and background pixels. The color profile of edges on the detected street is used to represent objects with respect to their surroundings. Thes...

Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and al...

We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition approaches can be approximated well by using a linear model. A linear model, built using a training set of face images, is specified in terms of a linear subspace spanned...

A new method for extraction and temporal segmentation of multiple motion trajectories in human motion is presented. The proposed method extracts motion trajectories generated by body parts without any initialization or any assumption on color distribution. Motion trajectories are very compact and representative features for activity recognition. Tr...

In surveillance situations, computer vision systems are often deployed to help humans perform their tasks more effectively. In a typical installation human observers are required to simultaneously monitor a number of video signals. Psychophysical research indicates that there are severe limitations in the ability of humans to monitor simultaneous s...

We present a system to retrieve all clips from a meet- ing archive that show a particular individual speaking, us- ing a single face or voice sample as the query. The sys- tem incorporates three novel ideas. One, rather than match the query to each individual sample in the archive, samples within a meeting are grouped first, generating a cluster of...

This paper presents a bottom-up approach that combines audio and video to simultaneously locate individual speakers in the video (2D source localization) and segment their speech (speaker diarization), in meetings recorded by a single stationary camera and a single microphone. The novelty lies in using motion information from the entire body rather...

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Text extraction in video documents, as an important research field of content-based information indexing and retrieval, has been developing rapidly since 1990s. This has led to much progress in text extraction, performance evaluation, and related applications. By reviewing the approaches proposed during the past five years, this paper introduces th...

The IEEE Computer Society will launch the Advanced Technology Executive Forum, an executive circle of high-profile and committed leaders from the computing industry, when the founding members hold their inaugural meeting in May 2008.

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Regeneration of templates from match scores has security and privacy implications related to any biometric authentication system. We propose a novel paradigm to reconstruct face templates from match scores using a linear approach. It proceeds by first modeling the behavior of the given face recognition algorithm by an affine transformation. The goa...

Establishing benchmark datasets, performance metrics and baseline algorithms have considerable research sig-nificance in gauging the progress in any application domain. These primarily allow both users and developers to compare the performance of various algorithms on a common platform. In our earlier works, we focused on developing performance met...

A biometric sample collected in an uncontrolled outdoor environment varies significantly from its indoor version. Sample variations due to outdoor environmental conditions degrade the performance of biometric systems that otherwise perform well with indoor samples. In this study, we quantitatively evaluate such performance degradation in the case o...

This paper presents an automated classification system for images based on their visual complexity. The image complexity is approximated using a clutter measure, and parameters for processing it are dynamically chosen. The classification method is part of a vision-based collision avoidance system for low altitude aerial vehicles, intended to be use...

A computer vision-based system using images from an airborne aircraft can increase flight safety by aiding the pilot to detect obstacles in the flight path so as to avoid mid-air collisions. Such a system fits naturally with the development of an external vision system proposed by NASA for use in high-speed civil transport aircraft with limited coc...

The use of biometric systems in physical access scenarios is gaining popularity. In such scenarios, users are enroled under well controlled conditions and the enrolment is usually indoors. To gain access to the building, the user provides his biometric samples in an outdoor environment over which there is little control. This adversely affects the...

Text detection and tracking is an important step in a video content analysis system as it brings important semantic clues which is a vital supplemental source of index information. While there has been a significant amount of research done on video text detection and tracking, there are very few works on performance evaluation of such systems. Eval...

The need for empirical evaluation metrics and algorithms is well acknowledged in the field of computer vision. The process leads to precise insights to understanding current technological capabilities and also helps in measuring progress. Hence designing good and meaningful performance measures is very critical. In this paper, we propose two compre...

Regeneration of biometric templates from match scores has security and privacy implications related to any biometric based authentication system. In this paper, we propose a novel non-iterative scheme to reconstruct face templates from match scores. We use an affine transformation of the images to approximate the behavior of the given face recognit...

In this work, we present a recently developed evaluation framework for video OCR specifically for English Text but could well be generalized for other languages as well. Earlier works include the de- velopment of an evaluation strategy for text detection and tracking in video, this work is a natural extension. We sucessfully port and use the ASR me...

Security and privacy issues remains a major hurdle in wide deployment of biometric based authentication system. For example, unauthorized access or regeneration of face templates has serious implications on the privacy of the concerned users. For robust and practical implementation of such system it is necessary to identify and explore the possible...

Segmenting different individuals in a group meeting and their speech is an important first step for various tasks such as meeting transcription, automatic camera panning, multimedia retrieval and monologue detection. In this effort, given a meeting room video, we attempt to segment individual person's speech and localize them in the video, based on...

Machine vision, also known as computer vision, is the scientific discipline whereby explicit, meaningful descriptions of physical objects from the world around us are constructed from their images. Machine vision produces measurements or abstractions from geometrical properties and comprises techniques for estimating features in images, relating fe...

We investigate methods to infer the best afine transformation based face recognition algorithm; which operates by projecting given images to a low-dimensional space, followed by distance computations. This category includes the following well known methods for recognition: the Principal Component Analysis (PCA), Linear Discriminant Analysis(LDA), a...

We propose a new support vector clustering (SVC) strategy by combining (SVC) with spectral graph partitioning (SGP). SVC has two main steps: support vector computation and cluster labeling using adjacency matrix. Spectral graph partitioning (SGP) method is applied to the adjacency matrix to determine the cluster labels. It is feasible to combine mu...

We propose a method for activity recognition based on multiple motion trajectories. Motion trajectories generated from body parts (hand, feet, and joints) are used as features. We not only recognize each activity but also temporally locate the start and end point of its duration. Input sequences are divided into separate temporal segments based on...

We propose a new method for extraction and temporal segmentation of multiple motion trajectories in human motion. Motion trajectories are very compact and representative features for activity recognition. Our method extracts motion trajectories generated by body parts without any initialization or any assumption on color distribution. Tracking huma...

In this paper, we propose a robust motion segmentation method using the techniques of matrix factorization and subspace separation. We first show that the shape interaction matrix can be derived using QR decomposition rather than Singular Value Decomposition(SVD) which also leads to a simple proof of the shape subspace separation theorem. Using the...

The detection of obstacles in the flight path of an aircraft is an important issue. Hundreds of lives are instantaneously lost when aircrafts collide. These collisions generally occur because of poor pilot visibility in bad weather conditions. Infrared imagery provides a solution to the problem since it is possible to detect targets that are occlud...

We propose methods for outlier handling and noise reduction using weighted local linear smoothing for a set of noisy points sampled from a nonlinear manifold. Weighted PCA is used as a building block for our methods and we suggest an iterative weight selection scheme for robust local linear fitting together with an outlier detection method based on...

The popularity of digital video is increasing rapidly. To help users navigate libraries of video, algorithms that automatically index video based on content are needed. One approach is to extract text appearing in video, which often reflects a scene's semantic content. This is a di#cult problem due to the unconstrained nature of general-purpose vid...

Despite advances in the archiving of digital video, we are still unable to efficiently search and retrieve the portions that interest us. Video indexing by shot segmentation has been a proposed solution and several research efforts are seen in the literature. Shot segmentation alone cannot solve the problem of content based access to video. Recogni...

This paper explores an approach for extracting scene text from a sequence of images with relative motion between the camera and the scene. It is assumed that the scene text lies on planar surfaces, whereas the other features are likely to be at random depths or undergoing independent motion. The motion model parameters of these planar surfaces are...

Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test...

The popularity of digital video is increasing rapidly. To help users navigate libraries of video, algo- rithms that automatically index video based on content are needed. One approach is to extract text appearing in video, which often reflects a scene's semantic content. This is a difficult problem due to the unconstrained na- ture of general-purpo...

Network Of Workstations (NOW) platforms put together with off-the-shelf workstations and networking hardware have become a cost effective, scalable, and flexible platform for video processing applications. Still, one has to manually schedule an algorithm to the available processors of the NOW to make efficient use of the resources. However, this ap...

The National Aeronautics and Space Administration (NASA), along with members of the aircraft industry, recently developed technologies for a new supersonic aircraft. One of the technological areas considered for this aircraft is the use of video cameras and image-processing equipment to aid the pilot in detecting other aircraft in the sky. The dete...

This paper presents a method for extracting multiple motion trajectories in human motions. We extract motion trajectories of body parts (hands and feet) using a new method based on optical flow information. This procedure is not sensitive to complicated backgrounds or color distribution of scenes. No body part model or skin color information is use...

Abstract Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications We propose a method for finding such text marks An exist - ing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions False alarm is reduced by introducing a binary im...

Wires can be hardly visible and thus present a serious hazard to rotorcrafts flying at low altitudes. Vision systems capable of detecting wires in time to avoid collisions must be able to find in the input images curves less than one or two pixels wide. This paper describes a study on the performance of wire detection using a sub-pixel edge detecto...

Various types of sensors have been developed for measuring the depth of liquids in tanks, such as a fuel tank in an aircraft. Almost all of these methods require the sensor to come in contact with the liquid with low-voltage electrical leads carrying the signal from the sensor to an external computer for processing. A particular concern when such i...

The high-speed civil transport (HSCT) aircraft has been designed with limited cockpit visibility. To handle this, the National Aeronautics and Space Administration (NASA) has proposed an external visibility system (XVS) to aid pilots in overcoming this lack of visibility. XVS obtains video images using high-resolution cameras mounted on and directe...

The need for content-based access to image and video information from media archives has captured the attention of researchers in recent years. Research efforts have led to the development of methods that provide access to image and video data. These methods have their roots in pattern recognition. The methods are used to determine the similarity i...

Document image analysis refers to algorithms and techniques that are applied to images of documents to obtain a computer-readable description from pixel data. A well-known document image analysis product is the Optical Character Recognition (OCR) software that recognizes characters in a scanned document. OCR makes it possible for the user to edit o...

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The continuous development of object detection algorithms is ushering in the need for evaluation tools to quantify algorithm performance. In this paper a set of seven metrics are proposed for quantifying different aspects of a detection algorithm's performance. The strengths and weaknesses of these metrics are described. They are implemented in the...

Many computes vision applications are computationally challenging especially when they need to meet real-time constraints. A major problem with special purpose systems is that they require the developers of image-processing applications to be aware of the low-level hardware design, making the task cumbersome. To avoid inflexible and expensive hardw...