Abstract: A moving object tracking system includes an input unit, a detection unit, a creating unit, a weight calculating unit, a calculating unit, and an output unit. The detection unit detects all tracking target moving objects from each of input images input. The creating unit creates a combination of a path that links each moving object detected in a first image to each moving object detected in a second image, a path that links each moving object detected in the first image to an unsuccessful detection in the second image, and a path that links an unsuccessful detection in the first image to each moving object detected in the second image. The calculating unit calculates a value for the combination of the paths to which weights are allocated. The output unit outputs a tracking result.

Abstract: According to one embodiment, a facial image search system including, search module configured to calculate degree of similarity between facial features extracted by feature extraction module and facial features contained in database and output search result based on calculated degree of similarity, measuring module configured to measure amount of search result output by search module, and selection module configured to sort out search result output by search module if amount of search result measured by measuring module is equal to or more than preset threshold.

Abstract: According to one embodiment, a facial image search system including attribute discrimination module configured to discriminate attribute based on facial feature extracted, a plurality of search modules configured to store facial feature as database in advance, add facial feature extracted to database, calculate degree of similarity between facial feature extracted and facial feature contained in database, setting module configured to generate setting information by associating with any attribute with information indicating search module, and control module configured to identify one or a plurality of search modules based on setting information and attribute and transmit facial feature extracted by feature extraction module to identified search modules.

Abstract: When groups of coordinates of face areas respectively contained in mutually different frames are within a predetermined error range, a face attribute assigning unit assigns mutually the same face attribute value to each of the face areas. In the case where a difference in the feature amounts between the frames is within a predetermined error range, a similar shot detecting unit detects that the shots from which the frames have respectively been extracted are similar shots to each of which mutually the same shot attribute value is assigned. In the case where it is judged that face areas that respectively appear in the frames contained in the similar shots and to which mutually different face attribute values have respectively been assigned represent the face of mutually the same person, the face attribute re-assigning unit assigns mutually the same face attribute value to each of the face areas.

Abstract: According to one embodiment, an image search apparatus includes, an image input module which is input with an image, an event detection module which detects events from the input image input by the image input module, and determines levels, depending on types of the detected events, an event controlling module which retains the events detected by the event detection module, for each of the levels, and an output module which outputs the events retained by the event controlling module, for each of the levels.

Abstract: There is provided a copying apparatus that copies a workpiece, including a shoe that comes into contact with a portion of the workpiece to be copied, and a first swiveling unit that swivels with the shoe in an arc pattern around a point, as a swiveling center, on a plane where the shoe comes into contact with the portion of the workpiece to be copied.

Abstract: According to one embodiment, an image processing device includes a readiness determining unit configured to determine whether or not a state of a face image included in an image at one time out of images obtained at a plurality of different times is a ready state that satisfies a condition for performing three-dimensionality determination, three-dimensionality determination is determining whether the object is three-dimensional or not; an initiation determining unit configured to determine whether or not a state of a face image included in an image at different time from the image at the one time is an initiation state changed from the ready state; and a first three-dimensionality determining unit configured to perform the three-dimensionality determination on the face images included in the images when it is determined that the state is the initiation state.

Abstract: According to one embodiment, an image processing device includes an obtaining unit configured to obtain a plurality of images captured in time series; a first calculating unit configured to calculate a first change vector indicating a change between the images in an angle representing a posture of a subject included in each of the images; a second calculating unit configured to calculate a second change vector indicating a change in coordinates of a feature point of the subject; a third calculating unit configured to calculate an intervector angle between the first change vector and the second change vector; and a determining unit configured to determine that the subject is three-dimensional when the intervector angle is smaller than a predetermined first threshold.

Abstract: A face recognition apparatus includes an image sequence acquiring unit, a face image acquiring unit, an intra-sequence classifying unit, an inter-sequence classifying unit, an identification unit, and a reference image storing unit. A plurality of cameras are attached in a corridor for monitoring one place with these cameras, so that when a plurality of moving people pass through, identification is performed for each moving people. Face images are classified into fragmental face image sets, and the fragmental face image sets are classified into integrated sets to achieve the identification.

Abstract: An object of the present invention is to provide a heavy metal removing apparatus which can efficiently remove the heavy metal contained in the dust produced by burning of the raw material containing the heavy metal, and a cement production system comprising the heavy metal removing apparatus. The heavy metal removing apparatus 10 comprises a cyclone separator 11 which separates exhaust gas containing the heavy metal from a part of the dust heated to a temperature equal to or more than a temperature at which the heavy metal can volatilize, a bag filter 13 which is connected to the subsequent stage of the cyclone separator 11 and separates the exhaust gas containing the heavy metal from the remainder of the dust, and a heavy metal removal tower 14 which is connected to the subsequent stage of the bag filter and removes the heavy metal from the exhaust gas.

Abstract: A pattern recognition method comprises steps of inputting a pattern of a recognition object performing feature extraction from the input pattern to generate a feature vector, increasing the number of quantization in an order from quantization number 1 or quantization number 2 to calculate a quantization threshold of each of the quantization number, wherein the quantization threshold of quantization number (n+1) using a quantization threshold of quantization number n (n>=1) is calculated and a quantization function having a quantization threshold corresponding to quantization number S (S>n) is generated, quantizing each component of the feature vector of the input pattern using the quantization function to generate an input quantization feature vector having each of the quantized component, storing a dictionary feature vector of the recognition object, or a quantized dictionary feature vector in which each component of the dictionary feature vector of the pattern of a recognition object is quantized; cal

Abstract: An object is identified by detecting an object area image of an object to be recognized from a degraded image, converting the object area image to a frequency area, extracting a feature vector which indicates the amount of blur, comparing the feature vector and a classified plurality of blurred images, obtaining a cluster which is the most similar to the feature vector, selecting one point spread function corresponding to the similar cluster, restoring the object area image to the image before being blurred using the point spread function, and comparing the restored image and a target image.

Abstract: The present invention provides an adhesive wheel balance weight capable of drastically reducing costs from those of conventional ones, and a process for producing the same. In an adhesive wheel balance weight (W) comprising a weight body (P) and an adhesive tape (T) for attaching the weight body (P) to a vehicle wheel, the weight body (P) comprises a folded weight comprising a folded metal plate piece. The folded weight of the present invention can be formed from a relatively inexpensive raw material sheet at a high yield rate. It is preferable that the raw material sheet is a zinc-coated steel sheet, because no rust-proofing aftertreatment is necessary and therefore further cost reduction is achieved, and its environmental burden is small.

Abstract: There is provided a copying apparatus that copies a workpiece, includes a shoe that is brought into contact with the workpiece, an air cylinder that enables moving the shoe in a vertical direction, a clamping mechanism that grasps the workpiece from side surfaces placed in a direction orthogonal to a traveling direction and, and a lateral translatory slide guide that slides the clamping mechanism in the direction.

Abstract: An apparatus for detecting a feature point includes an image input unit that inputs an image of the target object; a three-dimensional shape information holding unit that stores three-dimensional shape information including reference feature points of a model relating to the target object; a correspondence relation acquiring unit that acquires a correspondence relation between the input image and the three-dimensional shape; a seek area acquiring unit that acquires image information of a seek area on the input image corresponding to an area including a point corresponding to the specific feature point in the model on the basis of the correspondence relation; and a feature point detecting unit that detects the position of the specific feature point in the input image from the image information.

Abstract: Two TEGs are used for acquiring FET capacity. A first TEG includes a first base section of the same shape and same dimensions as a gate electrode of the FET whose capacity is to be acquired, and a first additional section added at one end of the first base section. A second TEG includes a second base section of the same shape and same dimensions as the first base section, a second additional section having the same shape and same dimensions as the first additional section and added to one end of the second base section, and a third additional section having the same shape and same dimensions as the second additional section and added to the other end of the second base section. The capacity between the body and source or between the body and drain of the FET whose capacity is to be acquired is estimated from the difference in capacity between the body and source or between the body and drain of the first TEG and second TEG.

Abstract: A person identifying apparatus calculates suitability as a reference for improving a face identification rate of an identical person appeared in frames of a moving image on the frame-to-frame basis, selects a frame from the moving image using the suitability, calculates a feature value from the selected frame, and identifies the face of the person on the basis of a similarity between the feature value and a feature value of a reference frame selected in advance using the suitability.

Abstract: This is a system having a personal identification function to perform a registering operation not as an explicit one. The system simplifies the confirmation of an identification result thereby to improve dictionary updating conveniences. A device control apparatus is configured to include a face identification processor, a device setting unit and an interactive processor. The device control apparatus is configured to acquire personal data on the face image of a user, to identify a person matching the acquired personal data, by comparing the acquired personal data and registered personal dictionary data, to display the face image, as matching the identified person, at the registration time on the basis of the registered personal dictionary data, to receive such confirmation information from the user as to confirm whether or not the displayed person is identical to the user, and to set device environment parameters matching the confirmed person.

Abstract: An object recognition apparatus in an embodiment includes an image input unit, an object detection unit, a diffuse reflection image generation unit, an object model storage unit, a difference image generation unit, a weight calculation unit, a weighted Gaussian filter application unit, a filter processing unit, and an identification unit. A weight to be assigned to a weighted Gaussian filter is determined in view of variations in lighting conditions and reflection components of pixels of an input image.

Abstract: A pattern recognition apparatus compares an image including a photographed object to be recognized with a model previously registered in a table and recognizes the object to be recognized, and the pattern recognition apparatus includes an image input part 1, a feature point extraction part 2, a triangulation part 3, a feature point selection part 4, a basis calculation part 5, a partial pattern structure part 6, an index calculation part 7, a table registration part 8, a pattern similarity calculation part 9, a hypothesis information generation part 10, and an object recognition part 11. Plural feature points are extracted from the image of the object to be recognized, triangulation of a feature point set is obtained, and a combination of plural feature points is selected from plural feature points in accordance with the extracted triangulation.