33 results about "N category" patented technology

To reduce the computation cost of rate / distortion optimization in image compression, the rate / distortion gradient of a frame of interest is classified to m categories. A category information creating unit acquires a threshold λ for a preceding frame as a predictive value λ′ for the frame of interest that is to be coded, and further finely segments a category in which the predictive value λ′ is included. A code amount is then calculated for each of n categories that include the predictive value λ′. A code sequence forming unit selects a category having a target rate, and searches for a threshold between an upper and a lower limit value of the category. A value (S) at the end of the processing is selected as the threshold λ, and a code sequence is formed by using the threshold λ.

The present invention discloses a method to construct template images for recognition, including the steps of: obtaining a plurality of digitized images belonging to n categories; for all categories, extracting common features for images belonging to a category; comparing common features of said category with common features of other categories other than category, to obtain discriminating features for the category; and including such features into representative features to obtain template images. A method to recognize an input image using the template images so obtained is also disclosed.

The invention discloses a method for a personalized recommendation of a Web text. The method comprises the following steps: performing feature extraction on a plurality of kinds of Web texts generated before a certain time t so as to obtain a feature matrix E of a Web text set, and then performing cluster so as to obtain n categories; besides, according to a time span hj from the time when a Web text oj in a Web text subset relevant to the behavior of a certain user ui before the time t to the time t, calculating out a preference influence degree dj to the user ui so as to obtain a pair of category number-influence degree cj of the Web text oj and generate a dynamic preference vector of the user ui; if the preference influence degree of the user and the category of the Web text to be recommended is found to be higher than or equal to a threshold value tan, recommending the Web text to be recommended to the user. According to the method disclosed by the invention, the dynamic influence changed with the time lapse of current preference from the historic behavior of the user is considered, and the method is more accurate in recommendation, has dynamic performance, and more conforms to the actual condition.

The invention is applicable to the field of computer vision, and provides an image retrieval method and an image retrieval device. The method includes extracting feature points of each image in an image set to create a feature point library; clustering the feature points in the feature point library to acquire N category, wherein the N is pre-defined as an integer larger than 0; extracting feature points of a to-be-retrieved image, predicating category of the to-be-retrieved image according to the feature points of the to-be-retrieved image, wherein the category is one of the N category; counting the occurrence frequency of N-category feature points in the to-be-retrieved image to acquire front M-category feature points with highest occurrence frequency, wherein the M is an integer larger than 0 but smaller than N; acquiring an image set corresponding to the category, counting the occurrence frequency of the M-category feature points in each image of the image set, and summing up the occurrence frequency to acquire values; outputting front L images with highest values, wherein the L is an integer larger than 0. By the image retrieval method and the image retrieval device, image retrieval results can be acquired rapidly and accurately.

The present invention provides an identity authentication method and system. The identity authentication method includes: transmitting electromagnetic waves of different frequencies to an object to be identified, and acquiring a plurality of S parameter; filter the S parameter and perform feature extraction, obtain at least one of the amplitude information, frequency information and phase information in the S parameter, and form a test set; use the S that contains n known objects The training sample set of parameter information trains the support vector machine classifier to generate a recognition model that includes n categories, each of which includes all S parameter information of a known object, where n is a positive integer; using the The recognition model recognizes the test set, and if the output result of the recognition model is one of the n categories, the object to be recognized passes the authentication. The authentication and identification of human body identity can be realized quickly and accurately by using the invention.

The invention provides a verification method which includes: by a verification server, receiving a verification request transmitted by a client; by the verification server, generating a verification page according to the verification request, wherein the verification page comprises N category areas and M element images, and N and M are positive integers; by the verification server, receiving correlation, between the N category areas and the M element images, built by a user; by the verification server, verifying according to the correlation. The verification method is simple to operate, high in man-machine interaction performance and high in safety, user experience can be improved effectively, and crack difficulty of verification codes is increased. The invention further provides the verification server.

The invention discloses a video key frame selecting method. The video key frame selecting method is characterized in that video frames can be divided into n categories by adopting a clustering method, and the categories are called F; a candidate key frame set C can be calculated; video information amount Ii represented by the candidate key frame ci can be calculated; the maximum candidate key frame ci of the video information amount Ii is selected to be the first key frame set S1; according to the formula .... the next key frame set Sk+1 can be calculated in an iterative manner; the video total information amount represented by the key frame set Sk+1 can be determined; and the key frame set Sk+1 can be output. Starting from the diversity of the key frame sets and the maximum information coverage angle, the key frame sets can be quickly and effectively selected from the classified video frames, and therefore the occurrence of the redundancy frames can be well prevented, and the lengths of the key frame sets can be determined automatically; the video key frame selecting method is simple and easy to realize, and the effect is good.

The invention relates to a method for automatically detecting string music trills, in particular to a method for detecting string music in real time during automatic music transcription so as to solve the problems that the trills have great influence on the automatic music transcription, and a traditional automatic music transcription method can not automatically detect the trills in the music during automatic string music transcription. According to the number of common diapason notes of the string music, the trills are classified into N categories, and the N categories of trill modules are trained into a matched object library through an audio recognition method, and audio signals of the music to be detected are inputted, and the characteristics of the audio signals are extracted to obtain a characteristic vector sequence; the average period of the counted trills is used as a length to segment the characteristic vector sequence, each vector sequence segment is recognized through theaudio recognition method, and time segments corresponding to the vector sequences of which continuous M or more than M segments are recognized as the same category of trills are detected to be the time segments of the thrills. The invention automatically detects the trills and eliminates the influence of the thrills on the automatic music transcription.