Review of constraints on vision-based gesture recognition for human–computer interaction

The ability of computers to recognise hand gestures visually is essential for progress in human-computer interaction. Gesture recognition has applications ranging from sign language to medical assistance to virtual reality. However, gesture recognition is extremely challenging not only because of its diverse contexts, multiple interpretations, and spatio-temporal variations but also because of the complex non-rigid properties of the hand. This study surveys major constraints on vision-based gesture recognition occurring in detection and pre-processing, representation and feature extraction, and recognition. Current challenges are explored in detail

Infant mortality rates regressed against number of vaccine doses routinely given: Is there a biochemical or synergistic toxicity?

The infant mortality rate (IMR) is one of the most important indicators of the socio-economic well-being and public health conditions of a country. The US childhood immunization schedule specifies 26 vaccine doses for infants aged less than 1 year—the most in the world—yet 33 nations have lower IMRs. Using linear regression, the immunization schedules of these 34 nations were examined and a correlation coefficient of r = 0.70 (p < 0.0001) was found between IMRs and the number of vaccine doses routinely given to infants. Nations were also grouped into five different vaccine dose ranges: 12–14, 15–17, 18–20, 21–23, and 24–26. The mean IMRs of all nations within each group were then calculated. Linear regression analysis of unweighted mean IMRs showed a high statistically significant correlation between increasing number of vaccine doses and increasing infant mortality rates, with r = 0.992 (p = 0.0009). Using the Tukey-Kramer test, statistically significant differences in mean IMRs were found between nations giving 12–14 vaccine doses and those giving 21–23, and 24–26 doses. A closer inspection of correlations between vaccine doses, biochemical or synergistic toxicity, and IMRs is essential

A novel set of features for continuous hand gesture recognition

Applications requiring the natural use of the human hand as a human–computer interface motivate research on continuous hand gesture recognition. Gesture recognition depends on gesture segmentation to locate the starting and end points of meaningful gestures while ignoring unintentional movements. Unfortunately, gesture segmentation remains a formidable challenge because of unconstrained spatiotemporal variations in gestures and the coarticulation and movement epenthesis of successive gestures. Furthermore, errors in hand image segmentation cause the estimated hand motion trajectory to deviate from the actual one. This research moves toward addressing these problems. Our approach entails using gesture spotting to distinguish meaningful gestures from unintentional movements. To avoid the effects of variations in a gesture’s motion chain code (MCC), we propose instead to use a novel set of features: the (a) orientation and (b) length of an ellipse least-squares fitted to motion-trajectory points and (c) the position of the hand. The features are designed to support classification using conditional random fields. To evaluate the performance of the system, 10 participants signed 10 gestures several times each, providing a total of 75 instances per gesture. To train the system, 50 instances of each gesture served as training data and 25 as testing data. For isolated gestures, the recognition rate using the MCC as a feature vector was only 69.6 % but rose to 96.0 % using the proposed features, a 26.1 % improvement. For continuous gestures, the recognition rate for the proposed features was 88.9 %. These results show the efficacy of the proposed method

A Bayesian explanation of the 'Uncanny Valley' effect and related psychological phenomena

There are a number of psychological phenomena in which dramatic emotional responses are evoked by seemingly innocuous perceptual stimuli. A well known example is the ‘uncanny valley’ effect whereby a near human-looking artifact can trigger feelings of eeriness and repulsion. Although such phenomena are reasonably well documented, there is no quantitative explanation for the findings and no mathematical model that is capable of predicting such behavior. Here I show (using a Bayesian model of categorical perception) that differential perceptual distortion arising from stimuli containing conflicting cues can give rise to a perceptual tension at category boundaries that could account for these phenomena. The model is not only the first quantitative explanation of the uncanny valley effect, but it may also provide a mathematical explanation for a range of social situations in which conflicting cues give rise to negative, fearful or even violent reactions

Offscreen and in the chair next to your: conversational agents speaking through actual human bodies

his paper demonstrates how to interact with a conversational agent that speaks through an actual human body face-to-face and in person (i.e., offscreen). This is made possible by the cyranoid method: a technique involving a human person speech shadowing for a remote third-party (i.e., receiving their words via a covert audio-relay apparatus and repeating them aloud in real-time). When a person shadows for an artificial conversational agent source, we call the resulting hybrid an “echoborg.” We report a study in which people encountered conversational agents either through a human shadower face-to-face or via a text interface under conditions where they assumed their interlocutor to be an actual person. Our results show that the perception of a conversational agent is dramatically altered when the agent is voiced by an actual, tangible person. We discuss the potential implications this methodology has for the development of conversational agents and general person perception research

Factors associated with preterm delivery and low birth weight: a study from rural Maharashtra, India

Background: Although preterm delivery and low birth weight (LBW) have been studied in India, findings may not be generalisable to rural areas such as the Marathwada region of Maharashtra state. There is limited information available on maternal and child health indicators from this region. We aimed to present some local estimates of preterm delivery and LBW in the Osmanabad district of Marathwada and assess available maternal risk factors. Methods: The study used routinely collected data on all in-hospital births in the maternity department of Halo Medical Foundation’s hospital from 1 (st )January 2008 to 31 (st )December 2014. Multivariable logistic regression analysis provided odds ratios (OR) with 95% confidence intervals (CI) for preterm delivery and LBW according to each maternal risk factor. Results: We analysed 655 live births, of which 6.1% were preterm deliveries. Of the full term births (N=615), 13.8% were LBW (<2.5 kilograms at birth). The odds of preterm delivery were three times higher (OR=3.23, 95% CI 1.36 to 7.65) and the odds of LBW were double (OR=2.03, 95% CI 1.14 to 3.60) among women <22 years of age compared with older women. The odds of both preterm delivery and LBW were reduced in multigravida compared with primigravida women regardless of age. Anaemia (Hb<11g/dl), which was prevalent in 91% of women tested, was not significantly related to these birth outcomes. Conclusions: The odds of preterm delivery and LBW were much higher in mothers under 22 years of age in this rural Indian population. Future studies should explore other related risk factors and the reasons for poor birth outcomes in younger mothers in this population, to inform the design of appropriate public health policies that address this issue

Avoiding the uncanny valley : robot appearance, personality and consistency of behavior in an attention-seeking home scenario for a robot companion

“The original publication is available at www.springerlink.com”. Copyright Springer. DOI: 10.1007/s10514-007-9058-3This article presents the results of video-based Human Robot Interaction (HRI) trials which investigated people’s perceptions of different robot appearances and associated attention-seeking features and behaviors displayed by robots with different appearance and behaviors. The HRI trials studied the participants’ preferences for various features of robot appearance and behavior, as well as their personality attributions towards the robots compared to their own personalities. Overall, participants tended to prefer robots with more human-like appearance and attributes. However, systematic individual differences in the dynamic appearance ratings are not consistent with a universal effect. Introverts and participants with lower emotional stability tended to prefer the mechanical looking appearance to a greater degree than other participants. It is also shown that it is possible to rate individual elements of a particular robot’s behavior and then assess the contribution, or otherwise, of that element to the overall perception of the robot by people. Relating participants’ dynamic appearance ratings of individual robots to independent static appearance ratings provided evidence that could be taken to support a portion of the left hand side of Mori’s theoretically proposed ‘uncanny valley’ diagram. Suggestions for future work are outlined.Peer reviewe

Service robotics: do you know your new companion? Framing an interdisciplinary technology assessment

Service-Robotic—mainly defined as “non-industrial robotics”—is identified as the next economical success story to be expected after robots have been ubiquitously implemented into industrial production lines. Under the heading of service-robotic, we found a widespread area of applications reaching from robotics in agriculture and in the public transportation system to service robots applied in private homes. We propose for our interdisciplinary perspective of technology assessment to take the human user/worker as common focus. In some cases, the user/worker is the effective subject acting by means of and in cooperation with a service robot; in other cases, the user/worker might become a pure object of the respective robotic system, for example, as a patient in a hospital. In this paper, we present a comprehensive interdisciplinary framework, which allows us to scrutinize some of the most relevant applications of service robotics; we propose to combine technical, economical, legal, philosophical/ethical, and psychological perspectives in order to design a thorough and comprehensive expert-based technology assessment. This allows us to understand the potentials as well as the limits and even the threats connected with the ongoing and the planned implementation of service robots into human lifeworld—particularly of those technical systems displaying increasing grades of autonomy

Judgment of the Humanness of an Interlocutor Is in the Eye of the Beholder

Despite tremendous advances in artificial language synthesis, no machine has so far succeeded in deceiving a human. Most research focused on analyzing the behavior of “good” machine. We here choose an opposite strategy, by analyzing the behavior of “bad” humans, i.e., humans perceived as machine. The Loebner Prize in Artificial Intelligence features humans and artificial agents trying to convince judges on their humanness via computer-mediated communication. Using this setting as a model, we investigated here whether the linguistic behavior of human subjects perceived as non-human would enable us to identify some of the core parameters involved in the judgment of an agents' humanness. We analyzed descriptive and semantic aspects of dialogues in which subjects succeeded or failed to convince judges of their humanness. Using cognitive and emotional dimensions in a global behavioral characterization, we demonstrate important differences in the patterns of behavioral expressiveness of the judges whether they perceived their interlocutor as being human or machine. Furthermore, the indicators of interest displayed by the judges were predictive of the final judgment of humanness. Thus, we show that the judgment of an interlocutor's humanness during a social interaction depends not only on his behavior, but also on the judge himself. Our results thus demonstrate that the judgment of humanness is in the eye of the beholder