Abstract: Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions. In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a state and the SOM output data. The state determination unit obtains a state evaluation value based on an activity value obtained by the activity value obtaining unit and the adaptability value. The time series estimation unit determines a state of an input data based on the state evaluation value and state transition probability between states. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions.

Abstract: A Self-Organizing Map learning device includes a distance calculator that obtains a distance D between an input vector in an observation space and a reference vector of each neuron in a latent space, a smallest value neuron specifier that specifies a smallest value neuron having the smallest distance D, a neuron selector that selects M (M is an integer smaller than L) selection neurons from the L (L is equal to or larger than 2) smallest value neurons in a case where the L smallest value neurons are present, and an updater that updates the reference vector of each neuron in the latent space with the M selection neurons as winner neurons.

Abstract: The position of a moving object is estimated with high accuracy using landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

Abstract: Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions (e.g., split image regions). In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a predetermined state and the SOM output data. The state determination unit determines a state of an input data. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions (e.g., split image regions).

Abstract: A state estimation apparatus obtains observation data sets for a tracking target object, and estimates an internal state of the object using likelihoods obtained from the observation data sets and the reliability of each observation data set. A first observation obtaining unit obtains first observation data. A second observation obtaining unit obtains second observation data. A first likelihood obtaining unit obtains a first likelihood based on the first observation data. A second likelihood obtaining unit obtains a second likelihood based on the second observation data. A likelihood combining unit obtains a combined likelihood based on the first and second likelihoods, first reliability data indicating the reliability of the first observation data, and second reliability data indicating the reliability of the second observation data.

Abstract: The position of a moving object is estimated with high accuracy based on landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

Abstract: The position of a moving object is estimated with high accuracy based on landmark information, and highly accurate state estimation is performed appropriately at high speed. A landmark detection unit obtains a distance between the moving object and each of two or more landmarks as landmark distance information based on observation data obtained by an observation obtaining unit. A candidate area obtaining unit determines a candidate area for a position of the moving object based on the landmark distance information obtained by the landmark detection unit, and obtains candidate area information indicating the determined candidate area. A state estimation unit estimates an internal state of the moving object based on the observation data, the landmark distance information, and the candidate area information to obtain moving object internal state estimation data, and estimates the environmental map based on the candidate area information and the landmark distance information to obtain environmental map data.

Abstract: In an object detection apparatus 1, a window definer 11 defines a window relative to the location of a pixel in an input image 20. A classification value calculator 13 calculates a classification value indicative of the likelihood that a detection target is present in the window image contained in the window based on the feature data of the detection target. A classification image generator 14 arranges the classification value calculated from the window image according to the pixel location to generate a classification image. An integrator 15 integrates the classification image and a past classification image 42 generated from a past input image input prior to the input image 20 to generate an integrated image 45. A determiner 16 determines whether the detection target is present in the input image 20 based on the integrated image 45.

Abstract: The object detection device 1 detects an object being recognized (such as a pedestrian) in a frame image 42, and identifies an area 42a where a detected object which is detected in the frame image 42 is present. A frame image 43 is input after the frame image 42. The object detection device 1 detects the object being recognized in the frame image 43, and identifies an area 43a where a detected object which is detected in the frame image 43 is present. When a distance from center coordinates 42b of the area 42a to center coordinates 43b of the area 43a is smaller than a reference distance, the object detection device 1 determines that the detected object which is detected in the frame image 43 is identical to the detected object which is detected in the frame image 42.

Abstract: A moving object controller efficiently generates an environmental map and performs highly accurate state estimation in a short time to appropriately control a moving object. An observation obtaining unit obtains observation data from an observable event. A landmark prediction unit generates a landmark prediction signal including predictive information about a landmark at a current time. A landmark detection unit detects information about the landmark at the current time, and generates a landmark detection signal indicating the detection result. A state estimation unit estimates an internal state of the moving object to obtain data indicating an estimated internal state of the moving object at the current time, and estimates the environmental map based on the landmark detection signal to obtain data indicating an estimated environmental map at the current time.

Abstract: The purpose of the present invention is to provide a state estimation apparatus that appropriately estimates the internal state of an observation target by determining likelihoods from a plurality of observations. An observation obtaining unit of the state estimation system obtains, at given time intervals, a plurality of observation data obtained from an observable event. The observation selecting unit selects a piece of observation data from the plurality of pieces of observation data obtained by the observation obtaining unit based on a posterior probability distribution data obtained at a preceding time t?1. The likelihood obtaining unit obtains likelihood data based on the observation data selected by the observation selecting unit and predicted probability distribution data obtained through prediction processing using the posterior probability distribution data.

Abstract: Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions. In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a state and the SOM output data. The state determination unit obtains a state evaluation value based on an activity value obtained by the activity value obtaining unit and the adaptability value. The time series estimation unit determines a state of an input data based on the state evaluation value and state transition probability between states. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions.

Abstract: Provided is a state estimation apparatus that enables more accurate and robust detection and tracking of an object by obtaining a plurality of sets of observation data for a tracking target object and estimating the internal state of the object using a plurality of likelihoods calculated from the obtained sets of observation data. The state estimation apparatus obtains first observation data and second observation data, each of which is composed of a plurality of pieces of observation data, and obtains possibility measurement data and necessity measurement data from the obtained plurality of pieces of observation data. In the state estimation apparatus, a likelihood obtaining unit obtains a first likelihood wp and a second likelihood wn from the possibility measurement data and the necessity measurement data. Using the obtained first likelihood wp and second likelihood wn enables the internal state of the object to be estimated.

Abstract: A state estimation apparatus appropriately estimates the internal state of an observation target by calculating a likelihood from observation data, and tracks, for example, multiple objects in a moving image and detects a new object and adds the object as a tracking target in an appropriate manner. A labeling unit detects a closed area from an observation image, and adds a label number to the closed area to generate a label image. A likelihood obtaining unit generates an object-erased image for new object detection by erasing image areas corresponding to all the currently-tracked objects. The apparatus performs the process for detecting a new object using the object-erased image for new object detection based on label numbers. The apparatus is appropriately prevented from erroneously determining that an area of the object-erased image for new object detection corresponding to the currently-tracked object and remaining after the erasure corresponds to a new object.

Abstract: Provided are a pixel interpolation apparatus, imaging apparatus, program, and integrated circuit that appropriately perform pixel interpolation on an image signal obtained by a single-chip image sensor with a four-color array filter whatever array pattern the four-color array filter has. An imaging apparatus includes an imaging circuitry, a signal processing circuitry, and a pixel interpolation processing circuitry. The apparatus calculates a degree of correlation for pairs in two orthogonal directions for an image signal obtained by the imaging circuitry including a single-chip image sensor having a four-color array filter using pixel data in an area around a target pixel, and performs pixel interpolation using the correlation degree as a determination criterion.

Abstract: Provided is a state determination apparatus that appropriately performs pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions (e.g., split image regions). In the state determination apparatus, the matching processing unit obtains adaptability data indicating a correlation degree between template data indicating a predetermined state and the SOM output data. The state determination unit determines a state of an input data. This allows for appropriately performing pattern classification processing and/or pattern determination processing even when a map generated by the SOM technique includes discontinuous image regions (e.g., split image regions).

Abstract: If the number of frames in a GOP of an input stream is not less than 15, the GOP is determined as a control unit time. If the number of frames in the GOP is less than 15, the following GOP is connected thereto until the number of frames becomes not less than 15 and the connected GOPs are determined as a control unit time. After correcting the control unit time, the average input bit rate Sn in each control unit time is obtained, and by using information on the input stream including the average input bit rate Sn, a quantization step value of an output stream is calculated.

Abstract: The object detection device 1 detects an object being recognized (such as a pedestrian) in a frame image 42, and identifies an area 42a where a detected object which is detected in the frame image 42 is present. A frame image 43 is input after the frame image 42. The object detection device 1 detects the object being recognized in the frame image 43, and identifies an area 43a where a detected object which is detected in the frame image 43 is present. When a distance from center coordinates 42b of the area 42a to center coordinates 43b of the area 43a is smaller than a reference distance, the object detection device 1 determines that the detected object which is detected in the frame image 43 is identical to the detected object which is detected in the frame image 42.

Abstract: An apparatus and method to detect a line segment or arc using Hough transform. A Hough transform unit performs contour extraction on brightness image data to generate contour image data, with pixels having a pixel value of 0 to 255, performs the Hough transform on points in the contour image data, and counts additional values represented by pixel values of points in the contour image data in a Hough table. The Hough transform unit performs contour extraction on first to third component data to generate first to third contour data with pixels having a pixel value of 0 to 255, performs the Hough transform on points in the first to third contour data, and counts additional values represented by pixel values of points in the first to third contour data in the Hough table. The detection unit comprehensively evaluates the counts to detect a line segment or arc.

Abstract: It is an object of the present invention to provide an image coding technique for suppressing degradation in image quality, in which the time and space where intra macroblocks appear are dispersed. A block count determination part determines the number of intra macroblocks to be allocated in each frame. A position determination part arranges the intra macroblocks at random positions in each frame. A coding part performs coding on the basis of the number of intra macroblocks to be allocated in a time direction, which is determined by the block count determination part, and the arrangement of the intra macroblocks in a spatial direction, which is determined by the position determination part, to thereby output compressed image data.