Skin detection in video under uncontrolled illumination

Multimedia Tools and Applications - Many vision-based human-computer interaction (HCI) applications require skin detection. However, their performance relies on accuracy in detecting skin regions...     

Too real for comfort? Uncanny responses to computer generated faces

As virtual humans approach photorealistic perfection, they risk making real humans uncomfortable. This intriguing phenomenon, known as the uncanny valley, is well known but not well understood. In an effort to demystify the causes of the uncanny valley, this paper proposes several perceptual, cognitive, and social mechanisms that have already helped address riddles like empathy, mate selection, threat avoidance, cognitive dissonance, and psychological defenses. In the four studies described herein, a computer generated human character’s facial proportions, skin texture, and level of detail were varied to examine their effect on perceived eeriness, human likeness, and attractiveness. In Study I, texture photorealism and polygon count increased human likeness. In Study II, texture photorealism heightened the accuracy of human judgments of ideal facial proportions. In Study III, atypical facial proportions were shown to be more disturbing on photorealistic faces than on other faces. In Study IV, a mismatch in the size and texture of the eyes and face was especially prone to make a character eerie. These results contest the depiction of the uncanny valley as a simple relation between comfort level and human likeness. This paper concludes by introducing a set of design principles for bridging the uncanny valley.     

Does social desirability bias favor humans? Explicit-implicit evaluations of synthesized speech support a new HCI model of impression management

Do people treat computers as social actors? To answer this question, researchers have measured the extent to which computers elicit social responses in people, such as impression management strategies for influencing the perceptions of others. But on this question findings in the literature conflict. To make sense of these findings, the present study proposes a dual-process model of impression management in human-computer interaction. The model predicts that, although machines may elicit nonconscious impression management strategies, they do not generally elicit conscious impression management strategies. One such strategy is presenting oneself favorably to others, which can be measured as social desirability bias when comparing self-reported preferences with implicit preferences. The current study uses both a questionnaire and an implicit association test (IAT) to compare attitudes toward human and machine speech. Although past studies on social desirability bias have demonstrated people’s tendency to underreport their preference for the preferred group when comparing two human groups, the current study found that, when comparing human speech and machine-synthesized speech, participants instead overreported their preference for the preferred (human) group. This finding supports the proposed dual-process model of impression management, because participants did not consciously treat computers as social actors.     

The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison

The Defense Advance Research Projects Agency Augmented Cognition program is developing innovative technologies that will transform human-computer interactions by making information systems adapt to the changing capabilities and limitations of the user. The first phase of the Augmented Cognition program was to empirically assess the ability of various psychophysiological measures to identify changes in human cognitive activity during task performance in real time. This overview describes the empirical results of a Technical Integration Experiment involving the evaluation of 20 psychophysiological measures from 11 different research groups, including functional Near Infrared imaging, continuous and event-related electrical encephalography, pupil dilation, mouse pressure, body posture, heart rate, and galvanic skin response. These "cognitive state gauges" were evaluated on a common, quasi-realistic, military command and control task called the Warship Commander Task. Participants monitored aircraft on a geographical display for their levels of threat and responded to the threatening ones, as they simultaneously monitored ship communications for ship status information. The task involves a combination of perceptual, motor, spatial, auditory, verbal, memory, and decision-making processing. Task load was manipulated by changing the quantity and types of aircraft appearing throughout the primary task and by varying the presence or absence of the secondary verbal-memory task. Eleven of the gauges significantly identified changes in cognitive activity during the task. This overview summarizes the results and examines the prospects for the successful transition of these cognitive state gauges to operational military human-machine systems.     

An Improved Usability Measure Based on Novice and Expert Performance

The novice–expert ratio method (NEM) pinpoints user interface design problems by identifying the steps in a task that have a high ratio of novice to expert completion time. This study tested the construct validity of NEM's ratio measure against common alternatives. Data were collected from 337 participants who separately performed 10 word-completion tasks on a cellular phone interface. The logarithm, ratio, Cohen's d, and Hedges's ? measures had similar construct validity, but Hedges's ? provided the most accurate measure of effect size. All these measures correlated more strongly with self-reported interface usability and interface knowledge when applied to the number of actions required to complete a task than when applied to task completion time. A weighted average of both measures had the highest correlation. The relatively high correlation between self-reported interface usability and a weighted Hedges's ? measure as compared to the correlations found in the literature indicates the usefulness of the weighted Hedges's ? measure in identifying usability problems.     

The uncanny valley does not interfere with level 1 visual perspective taking

When a computer-animated human character looks eerily realistic, viewers report a loss of empathy; they have difficulty taking the character’s perspective. To explain this perspective-taking impairment, known as the uncanny valley, a novel theory is proposed: The more human or less eerie a character looks, the more it interferes with level 1 visual perspective taking when the character’s perspective differs from that of the human observer (e.g., because the character competitively activates shared circuits in the observer’s brain). The proposed theory is evaluated in three experiments involving a dot-counting task in which participants either assumed or ignored the perspective of characters varying in their human photorealism and eeriness. Although response times and error rates were lower when the number of dots faced by the observer and character were the same (congruent condition) than when they were different (incongruent condition), no consistent pattern emerged between the human photorealism or eeriness of the characters and participants’ response times and error rates. Thus, the proposed theory is unsupported for level 1 visual perspective taking. As the effects of the uncanny valley on empathy have not previously been investigated systematically, these results provide evidence to eliminate one possible explanation.     

Memory-Based Attention Control for Activity Recognition at a Subway Station

We have developed a multicamera system, Digital City Surveillance, which uses a new calibration-free behavior recognition method for monitoring human activity at a subway station. We trained nine support vector machines from operator-classified data to recognize 512 combinations of events. Our method of attention control greatly reduced computation and increased classification accuracy     

Size constancy of adolescent schizophrenics.

In a size-constancy task 10 schizophrenic and 10 normal adolescent males judged variable triangles as smaller, same size, or larger than a standard. The schizophrenics' judgments were further from constancy, and differed qualitatively. They made more (a) same-size judgments, (b) changes of judgments, (c) overestimation of the size of the standard, and (d) improvement with practice. The relative constancy of the same-size judgments of most Ss suggested the effects of personality variables. A significant correlation was found between constancy performance and the Sc score on the MMPI for the experimental group. The direction of error, underconstancy or overconstancy, was determined by the space arrangement of the variable and the standard. Both groups responded similarly to the experimental conditions of distance, series order, and space arrangement. (22 ref.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Revisiting the uncanny valley theory: Developing and validating an alternative to the Godspeed indices

Mori (1970) proposed a hypothetical graph describing a nonlinear relation between a character’s degree of human likeness and the emotional response of the human perceiver. However, the index construction of these variables could result in their strong correlation, thus preventing rated characters from being plotted accurately. Phase 1 of this study tested the indices of the Godspeed questionnaire as measures of humanlike characters. The results indicate significant and strong correlations among the relevant indices (Bartneck, Kuli?, Croft, & Zoghbi, 2009). Phase 2 of this study developed alternative indices with nonsignificant correlations (p > .05) between the proposed y-axis eeriness and x-axis perceived humanness (r = .02). The new humanness and eeriness indices facilitate plotting relations among rated characters of varying human likeness.     

Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures

Japan has more robots than any other country with robots contributing to many areas of society, including manufacturing, healthcare, and entertainment. However, few studies have examined Japanese attitudes toward robots, and none has used implicit measures. This study compares attitudes among the faculty of a US and a Japanese university. Although the Japanese faculty reported many more experiences with robots, implicit measures indicated both faculties had more pleasant associations with humans. In addition, although the US faculty reported people were more threatening than robots, implicit measures indicated both faculties associated weapons more strongly with robots than with humans. Despite the media’s hype about Japan’s robot ‘craze,’ response similarities suggest factors other than attitude better explain robot adoption. These include differences in history and religion, personal and human identity, economic structure, professional specialization, and government policy. Japanese robotics offers a unique reference from which other nations may learn.

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