Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition

Spatio-temporal feature encoding is essential for encoding the dynamics in video sequences. Recurrent neural networks, particularly long short-term memory (LSTM) units, have been popular as an efficient tool for encoding spatio-temporal features in sequences. In this work, we investigate the effect of mode variations on the encoded spatio-temporal features using LSTMs. We show that the LSTM retains information related to the mode variation in the sequence, which is irrelevant to the task at hand (e.g. classification facial expressions). Actually, the LSTM forget mechanism is not robust enough to mode variations and preserves information that could negatively affect the encoded spatio-temporal features. We propose the mode variational LSTM to encode spatio-temporal features robust to unseen modes of variation. The mode variational LSTM modifies the original LSTM structure by adding an additional cell state that focuses on encoding the mode variation in the input sequence. To efficiently regulate what features should be stored in the additional cell state, additional gating functionality is also introduced. The effectiveness of the proposed mode variational LSTM is verified using the facial expression recognition task. Comparative experiments on publicly available datasets verified that the proposed mode variational LSTM outperforms existing methods. Moreover, a new dynamic facial expression dataset with different modes of variation, including various modes like pose and illumination variations, was collected to comprehensively evaluate the proposed mode variational LSTM. Experimental results verified that the proposed mode variational LSTM encodes spatio-temporal features robust to unseen modes of variation.Comment: Accepted in AAAI-1

The effect of functional roles on group efficiency

The usefulness of ‘roles’ as a pedagogical approach to support small group performance can be often read, however, their effect is rarely empirically assessed. Roles promote cohesion and responsibility and decrease so-called ‘process losses’ caused by coordination demands. In addition, roles can increase awareness of intra-group interaction. In this article, the effect of functional roles on group performance, efficiency and collaboration during computer-supported collaborative learning (CSCL) was investigated with questionnaires and quantitative content analysis of e-mail communication. A comparison of thirty-three questionnaire observations, distributed over ten groups in two research conditions: role (n = 5, N = 14) and non-role (n = 5, N = 19), revealed no main effect for performance (grade). A latent variable was interpreted as ‘perceived group efficiency’ (PGE). Multilevel modelling (MLM) yielded a positive marginal effect of PGE. Groups in the role condition appear to be more aware of their efficiency, compared to groups in the ‘non-role’ condition, regardless whether the group performs well or poor. Content analysis reveals that students in the role condition contribute more ‘task content’ focussed statements. This is, however, not as hypothesised due to the premise that roles decrease coordination and thus increase content focused statements; in fact, roles appear to stimulate coordination and simultaneously the amount of ‘task content’ focussed statements increases

On the exceptional damage-tolerance of gradient metallic materials

An experimental study is described on the fracture toughness and micro-mechanisms associated with the initiation and propagation of cracks in metallic nickel containing marked gradients in grain size, ranging from ∼30 nm to ∼4 μm. Specifically, cracks are grown in a gradient structured (GS) nickel with grain-size gradient ranging from the coarse macro-scale to nano-scale (CG → NG) and vice versa (NG → CG), with the measured crack-resistance R-curves compared to the corresponding behavior in uniform nano-grained (NG) and coarse-grained (CG) materials. It is found that the gradient structures display a much-improved combination of high strength and toughness compared to uniform grain-sized materials. However, based on J-integral measurements in the gradient materials, the crack-initiation toughness is far higher for cracks grown in the direction of the coarse-to-nano grained gradient than vice versa, a result which we ascribe primarily to excessive crack-tip blunting in the coarse-grained microstructure. Both gradient structures, however, display marked rising R-curve behavior with exceptional crack-growth toughnesses exceeding 200 MPa.m½