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In the process of aircraft residual ice detection based on near infrared spectrum method, the qualities of the images, such as brightness and contrast, are easily influenced by sunlight, weather and other factors. Therefore, it is hard to precisely match the feature points. In this paper, an improved Harris local invariant feature matching method is proposed. The improved Harris feature point detection...
The seismograph is a kind of seismic prospecting instrument, detection zone is nearly hundreds of meters. Along with the digital technology application in the engineering seismograph, need to collect and transfer a large of data, and efficient data transmission is directly related to exploration efficiency. Therefore, this paper proposes a parallel data concentrator based on the technology of FPGA,...
Various active learning methods have been proposed for image classification problems, while very little work addresses object detection. Measuring the informativeness of an image based on its object windows is a key problem in active learning for object detection. In this paper, an image selection method to select the most representative images is proposed based on measuring their object window distributions...
We consider the problem of segmenting objects in weakly labeled video. A video is weakly labeled if it is associated with a tag (e.g. Youtube videos with tags) describing the main object present in the video. It is weakly labeled because the tag only indicates the presence/absence of the object, but does not give the detailed spatial/temporal location of the object in the video. Given a weakly labeled...
Many people spend countless hours watching videos online or on TV. Current smart TV systems provide some basic two-way communications where users can interact with some features (e.g. browsing web, accessing social media, etc) provided by service providers. We would like to move beyond such primitive interactions and explore the possibility of allowing users to interact with \emph{video contents}...
Object detection is an important and challenging problem in the field of computer vision. Classical object detection approaches such as background subtraction and saliency detection do not require manual collection of training samples, but can be easily affected by noise factors, such as luminance changes and cluttered background. On the other hand, supervised learning based approaches such as Boosting...
By using intensity probability density and color invariance model, a novel feature-based color image watermarking method is proposed in this paper. Firstly, the uniform and robust feature points are extracted in the color invariance model by utilizing modified speeded up robust features (SURF) detector, in which the intensity probability density gradient is used instead of intensity gradient. Then,...
In this paper we develop an algorithm for action recognition and localization in videos. The algorithm uses a figure-centric visual word representation. Different from previous approaches it does not require reliable human detection and tracking as input. Instead, the person location is treated as a latent variable that is inferred simultaneously with action recognition. A spatial model for an action...
In this paper we present a morphologic edge detector using multidirectional structuring element approach for detecting edges of complex images under noisy condition. The experimental results show that the proposed edge detector has the desirable properties that a good edge detector should have. Comparative study reveals its detection performance exceeds conventional edge detectors and other morphologic...
In this paper a novel algorithm for detecting voltages of capacitors of cascade shunt active power filter (CSAPF) is presented based on Carrier Phase Shift-SPWM (CPS-SPWM). This work is motivated by the fact that the number of voltage sensors is largely increased by CSAPF with cascade topology which has been put into practical use for years especially in high voltage and high power drivers. Following...
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