Visible light communications (VLC) has the potential to play a major part in future smart home and next generation communication networks. There is significant ongoing work to increase the achievable data rates using VLC, to standardize it and integrate it within existing network infrastructures. The future of VLC systems depends on the ability to fabricate low cost transceiver components and to realize the promise of high data rates. This paper reports the design and fabrication of integrated transmitter and receiver components. The transmitter uses a two dimensional individually addressable array of micro light emitting diodes (μLEDs) and the receiver uses an integrated photodiode array fabricated in a CMOS technology. A preliminary result of a MIMO system implementation operating at a data rate of 1 Gbps is demonstrated. This paper also highlights the challenges in achieving highly parallel data communication along with the possible bottlenecks in integrated approaches.

We discuss important factors in the design of evaluation studies for systems that generate animations of American Sign Language (ASL) sentences. In particular, we outline how some cultural and linguistic characteristics of members of the American Deaf community must be taken into account so as to ensure the accuracy of evaluations involving these users. Finally, we describe our implementation and user-based evaluation (by native ASL signers) of a prototype ASL generator to produce sentences containing classifier predicates, frequent and complex spatial phenomena that previous ASL generators have not produced.

A method that combines shape-based object recognition and image segmentation is proposed for shape retrieval from images. Given a shape prior represented in a multi-scale curvature form, the proposed method identifies the target objects in images by grouping oversegmented image regions. The problem is formulated in a unified probabilistic framework, and object segmentation and recognition are accomplished simultaneously by a stochastic Markov Chain Monte Carlo (MCMC) mechanism. Within each sampling move during the simulation process, probabilistic region grouping operations are influenced by both the image information and the shape similarity constraint. The latter constraint is measured by a partial shape matching process. A generalized cluster sampling algorithm is presented in A. Barbu and S. Zhu (2003), combined with a large sampling jump and other implementation improvements, and greatly speeds up the overall stochastic process. The proposed method supports the segmentation and recognition of multiple occluded objects in images. Experimental results are provided for both synthetic and real images.