Manas Kamal Bhuyan

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Applications requiring the natural use of the human hand as a human–computer interface motivate research on continuous hand gesture recognition. Gesture recognition depends on gesture segmentation to locate the starting and end points of meaningful gestures while ignoring unintentional movements. Unfortunately, gesture segmentation remains a formidable(More)
The large shape variability and partial occlusions challenge most object detection and tracking methods for non- rigid targets such as pedestrians. Single camera tracking is limited in the scope of its applications because of the limited field of view (FOV) of a camera. This initiates the need for a multiple-camera system for completely monitoring and(More)
In this paper, a novel approach for hand pose recognition is proposed by analyzing the textures and key geometrical features of the hand. A skeletal hand model is constructed to analyze the abduction/adduction movements of the fingers and subsequently, texture analysis is performed to consider some inflexive finger movements. Probabilistic distributions of(More)
This paper describes a visual surveillance system for remote monitoring of unattended environments. For the purpose of efficiently tracking multiple people in the presence of occlusions, we propose: (i) to combine blob matching with particle filtering, and (ii) to augment these tracking algorithms with a novel colour appearance model. The proposed system(More)
An endoscope is a medical instrument that acquires images inside the human body. This paper proposes a new approach for the automatic detection of polyp regions in an endoscope image using a Hessian filter and machine learning techniques. Previous approaches tried to detect candidate polyp regions based on rectangular patches. But, a purely patch-based(More)