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The purpose of our demo is to show the application and performance of some low-complexity image descriptors in object recognition under realistic circumstances. We built a client-server system where several image retrieval methods and image segmentation approaches can be tested with the help of a network connected Android device (mobile phone, table or head mounted computer). A modified version of the CEDD (Color and Edge Directivity Descriptor) is proposed, as the most robust lightweight descriptor found in our tests, and manual or saliency based object selection are also included. The main purpose of the demo is to show the possibilities of lightweight object recognition with the modified descriptor and different object segmentation.

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In our article we deal with the simultaneous problem of reconstruction and recognition of binary symbols loaded with heavy additive noise. We introduce a Markov Random Field (MRF) model where a shape energy term is responsible to find a solution similar to a tested hypothesis. This way we could increase the precision of the reconstruction process the only question is how to find out the right hypotheses which helps the reconstruction the best way. Fortunately the new energy term gives us the answer: the tested hypotheses with the minimal shape energy component designates the right shape.

In modern societies new, lifestyle related chronic diseases are appearing, affecting more and more people. Besides decreasing the quality of life for these patients, their treatments require increasing financial and social support from governments (and in many cases, even from the patients themselves). Apart from socioeconomic concerns, another serious problem is the increasing shortage of experts (e.g. doctors, dietitians, ergonomists) that could help people, as the need for them is growing faster than their numbers. In this paper, a framework for creating expert systems capable of containing and properly using the knowledge of such experts, for providing help to users in acquiring and maintaining a healthy lifestyle, is presented. By selecting two different areas, diet and physical oriented lifestyle management and workplace related ergonomics, the effectiveness of such systems is tested.