Abstract-Animals leaving the forest area and entering the human habitat is increasing day by day. Animals entering the agricultural areas placed near the forest destroy crops or even attack on people therefore there is a need of system which detects the animal presence and gives warning about that in the view of security purpose. In this paper wild animal which enters the human habitation are recognized. The movement of animals in the input video is detected using Foreground detector algorithm. Extraction of foreground animal is done using Back ground subtraction based Gaussian mixture model. Morphological filters are used to remove the noise from binary image obtained from background subtraction. Training and recognition is done using back propagation algorithm. If trained images are matched with the test image, then the animal is recognized. The project aims to safe guard the wild life and animal life and it is a great help to forest department.
This paper proposes a method to embed multiple features of an image for object localization and salient region for object detection and tracking. Initially, the object location is obtained using ground truth and features are extracted. Subsequently, these features are used to find the potential area of an object and this area is used to identify a salient region. The pixels color and gradients are used as feature matrix and saliency maps are generated using the visual cue like the local contrast. The salient region detection has proved its application in object recognition and segmentation. The combination of feature matrix and saliency map enables the proposed tracker to be robust. The proposed method efficiently localizes the object even when there are scaling, rotation and illumination changes. The experiments are conducted using publicly available Visual object tracking (VOT) 2016 dataset which consists of many challenging video sequences and the proposed method provided competitive results when compared to many state-of-the-art methods which is evaluated using the Visual object tracking toolkit.
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