Animal Detection

  Monitoring wild animals became easy due to camera trap network, a technique to explore animal life using automatically triggered camera on the presence of animal and yields a large volume of multimedia data. Animal detection is a dynamic research field since the last several decades. In this paper, we propose a animal detection system to monitor wildlife and detect wild animals from highly cluttered natural images. The data acquired from the camera-trap network comprises of scenes that are highly cluttered that poses a challenge for detection of wild animals bringing about low recognition rates and high false discovery rates....

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Attendance of all Students in a Class using Face Detection

  The most arduous task in any organization is attendance marking. In this project we proposed an automated attendance management system which tackles the predicament of recognition of faces in biometric systems subject to different real time scenarios such as illumination, rotation and scaling. This model incorporates a camera that captures input image, an algorithm to detect a face from the input image, encode it and recognize the face and mark the attendance in database and convert it into PDF file. The camera captures the image and sends it to the server where faces are recognized and attendance is calculated on basis of it.....

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Hand Gesture Recognition

  Hand gesture recognition is very significant for human-computer interaction. In this work, we present a novel real-time method for hand gesture recognition. In our framework, the hand region is extracted from the background with the background subtraction method. Then, the palm and fingers are segmented so as to detect and recognize the fingers. Finally, a rule classifier is applied to predict the labels of hand gestures.Hand Gesture Recognition (HGR) targets on interpreting the sign language into text or speech, so as to facilitate the communication between deaf-mute people and ordinary people. This task has broad social impact, but is still very challenging due to the complexity and large variations in hand actions. Existing methods for HGR use hand-crafted features to describe sign language motion and build classification models based on those features.

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