Negligible penalty all-optical routing using a 12 × 12 passive InP wavelength-selective router

This work demonstrates transmission at 2.5 Gbit/s across two wavelength-division multiplexing (WDM) network nodes, constructed using counter-propagating semiconductor optical amplifier (SOA) wavelength converters and an integrated wavelength-selective router separated by 45 km of fiber, with an overall penalty of 0.6 dB. Minimal degradation of the eye diagram is evident across the whole system. Full utilization of the capacity of the router would allow an aggregate 360-Gbit/s node capacity for a WDM channel of 2.5 Gb/s.

Human-humanoid interaction: Is a humanoid robot perceived as a human?

As humanoid robots become more commonplace in our society, it is important to understand the relation between humans and humanoid robots. In human face-to-face interaction, the observation of another individual performing an action facilitates the execution of a similar action, and interferes with the execution of different action. This phenomenon has been explained by the existence of shared internal representations for the execution and perception of actions, which would be automatically activated by the perception of another individual's action. In one interference experiment, null interference was reported when subjects observed a robotic arm perform the incongruent task, suggesting that this effect may be specific to interacting with other humans. This experimental paradigm, designed to investigate motor interference in human interactions, was adapted to investigate how similar the implicit perception of a humanoid robot is to a human agent. Subjects performed rhythmic arm movements while observing either a human agent or humanoid robot performing either congruent or incongruent movements. The variance of the executed movements was used as a measure of the amount of interference in the movements. Both the human and humanoid agents produced significant interference effect. These results suggest that observing the action of humanoid robot and human agent may rely on similar perceptual processes. Furthermore, the ratio of the variance in incongruent to congruent conditions varied between the human agent and humanoid robot. We speculate this ratio describes how the implicit perception of a robot is similar to that of a human, so that this paradigm could provide an objective measure of the reaction to different types of robots and be used to guide the design of humanoid robots interacting with humans. © 2004 IEEE.

MCBoost: Multiple classifier boosting for perceptual co-clustering of images and visual features

We present a new co-clustering problem of images and visual features. The problem involves a set of non-object images in addition to a set of object images and features to be co-clustered. Co-clustering is performed in a way that maximises discrimination of object images from non-object images, thus emphasizing discriminative features. This provides a way of obtaining perceptual joint-clusters of object images and features. We tackle the problem by simultaneously boosting multiple strong classifiers which compete for images by their expertise. Each boosting classifier is an aggregation of weak-learners, i.e. simple visual features. The obtained classifiers are useful for object detection tasks which exhibit multimodalities, e.g. multi-category and multi-view object detection tasks. Experiments on a set of pedestrian images and a face data set demonstrate that the method yields intuitive image clusters with associated features and is much superior to conventional boosting classifiers in object detection tasks.