By Ana Paiva, Rui Prada, Rosalind W. Picard
This booklet constitutes the refereed complaints of the second one foreign convention on Affective Computing and clever interplay, ACII 2007, held in Lisbon, Portugal, in September 2007.
The fifty seven revised complete papers and four revised brief papers provided including the prolonged abstracts of 33 poster papers have been rigorously reviewed and chosen from 151 submissions. The papers are equipped in topical sections on affective facial features and popularity, affective physique expression and popularity, affective speech processing, affective textual content and discussion processing, recognising have an effect on utilizing physiological measures, computational types of emotion and theoretical foundations, affective databases, annotations, instruments and languages, affective sound and song processing, affective interactions: platforms and functions, in addition to comparing affective systems.
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Extra info for Affective Computing and Intelligent Interaction: Second International Conference, ACII 2007, Lisbon, Portugal, September 12-14, 2007, Proceedings
Avatar front view (b) (c) Fig. 4. 2 PEP Extraction for Pseudo Facial Expression Database Based on the above facial points annotation result, 12 PEP parameters are then extracted by measuring the movement of facial points as defined in Table 3. 3 for Table 3. 2 Units (FAPU) ENS ES AU IRISD AU AU MNS MNS MNS MW MNS MW Facial Expression Synthesis Using PAD Emotional Parameters 29 Table 4. Sample number of 7 expressions (labels in the first row) in each PEP clustering center (Ci in the first column) C1 C2 C3 C4 C5 C6 C7 Total C1 HAP 25 4 2 0 0 0 0 31 C2 C3 C4 C5 C6 C7 SUP 1 20 0 6 0 3 0 30 ANG 2 1 18 1 0 0 8 30 NEU 0 0 0 30 0 0 0 30 SAD 1 0 9 0 15 4 2 31 FEAR 0 3 4 0 9 11 5 32 DIS Total 0 29 1 29 45 12 0 37 2 26 2 20 27 12 29 213 Fig.
The pseudo expression database containing the PAD annotation as well as PEP configuration is used to train the PAD-PEP mapping model. In order to find a proper emotion-expression mapping function between PAD and PEP, we have tried the polynomial function with the first and second order as well as non-linear exponential function. As the experimental result reveals, it is the second order polynomial function that receive the best fitting result, and the mathematic form is shown in Equation 2. e. [P2, A2, D2], α and β are the corresponding coefficient matrix, δ is the constant offset vector.
The agent’s utterances do not change between animations, even if in the real-life verbal communication is usually modiﬁed according to the values of power and distance (see section 3). In this experiment we aimed at measuring the eﬀect of facial expressions only, thus we had to avoid the inﬂuence that diﬀerent verbal messages might have on the subjects’ evaluation. For this purpose we decided to use “neutral-style” utterances, which are identical for all animations. The subjects were informed about 20 R.