34results about How to "Moderate computational complexity" patented technology

A human behavior recognition method based on mobile devices, which uses a variety of sensors built in mobile devices to collect data in real time; performs a series of data preprocessing operations such as correction, filtering, calculation and data generation, and data segmentation on the data obtained by the sensors; Feature extraction is performed on the processed data segment, and the extracted corresponding feature vector is input into the device location classification model to obtain the device location category; the corresponding behavior classification model is selected according to the obtained device location category, and the extracted corresponding feature vector is input into the behavior classification model, Obtain the final behavior recognition result. The invention provides a mobile device-based human behavior recognition method with good versatility and high accuracy.

The invention discloses an FPGA (Field Programmable Gate Array)-based infrared remote sensing image real-time target detection method. The method mainly aims at solving the problems of high omission ratio, multiple false alarms, poor robustness and the like of the existing ship detection algorithm. The method is mainly composed of a coarse detection module based on a gradient convolution model anda fine detection module based on Fourier spectrum and SVM. According to the invention, the ship target and typical false alarm characteristics in the infrared remote sensing image are fully analyzed,and available features capable of effectively distinguishing ship targets and typical false alarms are selected, and an accurate and simple target classification model is constructed in combination with a support vector machine classification algorithm, and quick and accurate elimination of the false alarms is realized in combination with two-dimensional Fourier transform. Meanwhile, consumptionof FPGA logic resources and storage resources can be reduced, and the advantage of FPGA parallel control is brought into play, so that high-precision target detection is completed under the conditionthat few FPGA resources are occupied.

The invention discloses a feature extraction method of a two-dimensional image. The method includes the following steps: S1, obtaining Gabor filter differential decomposition for a texture image, and obtaining a set of binary images; S2, using statistical calculation for the decomposed binary image Sub-extracting texture features; S3, using principal component analysis to reduce dimensionality of the extracted texture feature vectors, and performing texture classification and retrieval on the feature vectors after dimensionality reduction. The present invention has the advantage of not needing to define texture primitives, and the calculation complexity is moderate. The newly proposed five statistical operators more comprehensively describe the decomposed texture primitives and the arrangement rules of primitives, and in the recognition process , the introduction of the principal component analysis algorithm increases the calculation speed of the method and is applicable to the real-time retrieval and classification of texture images.