Diganta Baruah

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In this paper, a new online evolving clustering approach for streaming data is proposed, named Dynamically Evolving Clustering method. The clustering approach attempts to meet the following three key requirements of data stream clustering: (i) fast and memory efficient (ii) adaptive (iii) robust to noise. The proposed clustering approach processes one(More)
In this paper we address the problem of human activity recognition based only on acoustic modality. The ultimate goal is continuous acoustic monitoring of public places like parks and bus stops for detecting littering activities so that the people involved in such acts can be prompted to bin appropriately. We exploit the fact that when human interacts with(More)
This paper reviews the comparative performance of Support Vector Machine (SVM) using four different kernels, i.e., Linear, Polynomial, Radial Basis Function (RBF) and Sigmoid. Overall accuracy (OA), Kappa Index Analysis (KIA), Receiver Operating Characteristic (ROC) and Precision (P) have been considered as evaluation parameters in order to assess the(More)
In this paper we investigate the application of ensemble of one-class classifiers to the problem of acoustic event classification. We present some initial results that are based on acoustic signals emitted by different litter causing material when contacted by human. When a person interacts with objects made with specific material, characteristic sounds are(More)
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