Georgiana Simion

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The recognition of hand gestures from image sequences is an important and challenging problem. This paper presents a robust solution to track and recognize a list of hand gestures from their trajectory. The main tools of the proposed solution are robust kernel density estimation and the related mean shift algorithm, used in both video tracking and(More)
This work proposes a compositional approach to hand posture recognition, using sparse features. The hand posture is decomposed into relevant compositions which are learned for each hand posture class without supervision; no hand segmentations or localization during training is needed. To learn relevant composition prototypes, an entropy range maximization(More)
New results obtain with the compositional technique for hand posture recognition is presented. Compositional methods are a powerful approach in image understanding. Most papers using this concept address image categorization problems. We recently propose a hand pose recognition method using the compositional approach. In this paper we present further(More)
– The Lidar (LIght Detection And Ranging) sensor produced by Siemens uses five infrared beams to detect targets up to a distance of approximately 250 m. The paper describes the tests witch has been develop using our new software in order to visualize the detected targets. We used our program in the detection of different types of targets, placed at(More)
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