Design of a Wireless Vision Sensor for Object Tracking in Wireless Vision Sensor Networks

The integration of CMOS cameras with embedded processors and wireless communication devices has enabled the development of distributed wireless vision systems. Wireless Vision Sensor Networks (WVSNs), which consist of wirelessly connected embedded systems with vision and sensing capabilities, provide wide variety of application areas that have not been possible to realize with the wall-powered vision systems with wired links or scalar-data based wireless sensor networks. In this paper, the design of a middleware for a wireless vision sensor node is presented for the realization of WVSNs. The implemented wireless vision sensor node is tested through a simple vision application to study and analyze its capabilities, and determine the challenges in distributed vision applications through a wireless network of low-power embedded devices. The results of this paper highlight the practical concerns for the development of efficient image processing and communication solutions for WVSNs and emphasize the need for cross-layer solutions that unify these two so-far-independent research areas.

The Perception of Natural, Cell Phone, and Computer-Synthesized Speech During The Performance Of Simultaneous Visual-Motor Tasks

This study investigated the influence of top-down and bottom-up information on speech perception in complex listening environments. Specifically, the effects of listening to different types of processed speech were examined on intelligibility and on simultaneous visual-motor performance. The goal was to extend the generalizability of results in speech perception to environments outside of the laboratory. The effect of bottom-up information was evaluated with natural, cell phone and synthetic speech. The effect of simultaneous tasks was evaluated with concurrent visual-motor and memory tasks. Earlier works on the perception of speech during simultaneous visual-motor tasks have shown inconsistent results (Choi, 2004; Strayer & Johnston, 2001). In the present experiments, two dual-task paradigms were constructed in order to mimic non-laboratory listening environments. In the first two experiments, an auditory word repetition task was the primary task and a visual-motor task was the secondary task. Participants were presented with different kinds of speech in a background of multi-speaker babble and were asked to repeat the last word of every sentence while doing the simultaneous tracking task. Word accuracy and visual-motor task performance were measured. Taken together, the results of Experiments 1 and 2 showed that the intelligibility of natural speech was better than synthetic speech and that synthetic speech was better perceived than cell phone speech. The visual-motor methodology was found to demonstrate independent and supplemental information and provided a better understanding of the entire speech perception process. Experiment 3 was conducted to determine whether the automaticity of the tasks (Schneider & Shiffrin, 1977) helped to explain the results of the first two experiments. It was found that cell phone speech allowed better simultaneous pursuit rotor performance only at low intelligibility levels when participants ignored the listening task. Also, simultaneous task performance improved dramatically for natural speech when intelligibility was good. Overall, it could be concluded that knowledge of intelligibility alone is insufficient to characterize processing of different speech sources. Additional measures such as attentional demands and performance of simultaneous tasks were also important in characterizing the perception of different kinds of speech in complex listening environments.