Abstract. In this paper, we propose a real-time algorithm for counting people from depth image sequences acquired using the Kinect sensor. Counting people in public vehicles became a vital research topic. Information on the passenger flow plays a pivotal role in transportation databases. It helps the transport operators to optimize their operational costs, providing that the data are acquired automatically and with sufficient accuracy. We show that our algorithm is accurate and fast as it allows 16 frames per second to be processed. Thus, it can be used either in real-time to process traffic information on the fly, or in the batch mode for analyzing very large databases of previously acquired image data.
Abstract. Heterogeneity is a well-recognized feature of malignancy associated with increased tumor aggression and treatment resistance. Texture analysis (TA) of images of various modalities, including, among others, CT, MRI or PET, can be applied to quantify the tumor heterogeneity and to extract useful information from images acquired in routine clinical practice without additional radiation or expense of further procedures. In this paper, we elaborate on the filtration-based approach to TA applied for extracting features from large sets of simulated images reflecting various clinical circumstances. The areas under receiver operating characteristic curves were used to assess the diagnostic performance of the derived biomarkers. We present and discuss their discriminative abilities in identifying heterogeneity and classifying images with simulated lesions of various characteristics and localized density variations.
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