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There is a large demand in the area of video-surveillance, especially in people detection, which has caused a large increase in the number of researches and resources in this field. As training images and annotations are not always available, it is important to consider the cost involved in creating the detector models. For example, for elderly people detection, the detector must have into account...
For its simplicity and ease of implementation, Energy detection (ED) is attractive for spectrum sensing in cognitive radio (CR) systems. In ED, the energy captured is compared against a fixed detection threshold, which is estimated as a function of the noise power. Uncertainties caused by the imperfect knowledge of the noise power, referred to as noise uncertainty, leads to a reduced performance of...
The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our...
In this paper an improved real time algorithm for detecting pedestrians in surveillance video is proposed. The algorithm is based on people appearance and defines a person model as the union of four models of body parts. Firstly, motion segmentation is performed to detect moving pixels. Then, moving regions are extracted and tracked. Finally, the detected moving objects are classified as human or...
The appearance-based approach to face detection has seen great advances in the last several years. In this approach, we learn the image statistics describing the texture pattern (appearance) of the object class we want to detect, e.g., the face. However, this approach has had limited success in providing an accurate and detailed description of the internal facial features, i.e., eyes, brows, nose,...
The proposed method detects fetal R waves on abdominal non-invasive records. An exponentially averaged pattern of the mother PQRST segment is obtained and subtracted. Subsequently the fetal R detector based on a Smoothed Nonlinear Energy Operator (SNEO) is applied to the residual signal. Finally, criteria about amplitude, heart rate and backward search are settled to correct false detections. To evaluate...
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