Abstract: A system of detection, tracking and identification of an evolutionary adaptation of a vehicle lamp includes an image capture device and a processor. The image capture device captures an image of a vehicle. The processor processes the image of the vehicle to generate a detection result of the vehicle lamp, analyzes and integrates vehicle lamp dynamic motion information and vehicle lamp multiple scale variation information based on the detection result, and then tracks the position of the vehicle lamp by applying a multiple scale vehicle lamp measurement model.

Abstract: A system of detection, tracking and identification of an evolutionary adaptation of a vehicle lamp includes an image capture device and a processor. The image capture device captures an image of a vehicle. The processor processes the image of the vehicle to generate a detection result of the vehicle lamp, analyzes and integrates vehicle lamp dynamic motion information and vehicle lamp multiple scale variation information based on the detection result, and then tracks the position of the vehicle lamp by applying a multiple scale vehicle lamp measurement model.

Abstract: A multi-class object classifying method and system are disclosed herein, where the multi-class object classifying method includes the following steps: classes, first training images and second training images are received and stored, and first characteristic images and second characteristic images are respectively extracted from the first training images and the second training images; the first training images is used to generate classifiers through a linear mapping classifying method; a classifier and the second characteristic images are used to determine parameter ranges corresponding to the classes and a threshold corresponding to the classifier.

Abstract: A multi-class object classifying method and system are disclosed herein, where the multi-class object classifying method includes the following steps: classes, first training images and second training images are received and stored, and first characteristic images and second characteristic images are respectively extracted from the first training images and the second training images; the first training images is used to generate classifiers through a linear mapping classifying method; a classifier and the second characteristic images are used to determine parameter ranges corresponding to the classes and a threshold corresponding to the classifier.

Abstract: A pedestrian detection system of detecting whether there is a pedestrian in a scene, the pedestrian detection system includes an image-capturing module, a preprocessing module, a human detection module, an image-stitching module and a decision module. The image-capturing module is configured for generating a plurality of first detection image data according to a contrast decision result. The preprocessing module is configured for generating a plurality of first image skeleton data according to the first detection image data. The human detection module is configured for generating a plurality of second image skeleton data. The image-stitching module is configured for stitching the plurality of first detection image data to generate at least one third detection image data. The decision module is configured for generating and outputting a detection result according to the third detection image data. A pedestrian detection method is disclosed herein as well.

Abstract: An image processing method and system using the same, wherein the image processing method includes capturing a plurality of images corresponding to the surroundings of an object using a plurality of image capturing modules to generate a two-dimension planar image; providing a three-dimension projected curved surface; defining a plurality of first grids on the three-dimension projected curved surface and a plurality of second grids on the two-dimension planar image, wherein each of the first grids correspond to each of the second grids; transforming the first grids on the three-dimension projected curved surface and the second grids on the two-dimension planar image into a plurality of first redrawn grids and second redrawn grids respectively based on the angles formed between the normal vector of the two-dimension planar image and the normal vector of each first grid, wherein each first redrawn grid corresponds to each second redrawn grid.

Abstract: A building texture extracting apparatus and a method thereof are provided, wherein the building texture extracting apparatus comprises a storage unit and a processor. The storage unit is configured to store an aerial image and a panoramic image of a building. There is a coordinate correlation between the aerial image and the panoramic image. The processor defines an edge segment of a building in the aerial image, calculates an edge function according to the edge segment, projects the edge function onto the panoramic image according to the coordinate correlation to derive an edge curve function, decides an edge curve segment according to the edge curve function, captures an image area under the edge curve segment to be a building texture of the building, and stores the building texture in the storage unit.

Abstract: A pedestrian detection system of detecting whether there is a pedestrian in a scene, the pedestrian detection system includes an image-capturing module, a preprocessing module, a human detection module, an image-stitching module and a decision module. The image-capturing module is configured for generating a plurality of first detection image data according to a contrast decision result. The preprocessing module is configured for generating a plurality of first image skeleton data according to the first detection image data. The human detection module is configured for generating a plurality of second image skeleton data. The image-stitching module is configured for stitching the plurality of first detection image data to generate at least one third detection image data. The decision module is configured for generating and outputting a detection result according to the third detection image data. A pedestrian detection method is disclosed herein as well.

Abstract: An image processing method and system using the same, wherein the image processing method includes capturing a plurality of images corresponding to the surroundings of an object using a plurality of image capturing modules to generate a two-dimension planar image; providing a three-dimension projected curved surface; defining a plurality of first grids on the three-dimension projected curved surface and a plurality of second grids on the two-dimension planar image, wherein each of the first grids correspond to each of the second grids; transforming the first grids on the three-dimension projected curved surface and the second grids on the two-dimension planar image into a plurality of first redrawn grids and second redrawn grids respectively based on the angles formed between the normal vector of the two-dimension planar image and the normal vector of each first grid, wherein each first redrawn grid corresponds to each second redrawn grid.

Abstract: A locating apparatus, a locating method and a computer program storage product thereof for a mobile device are provided. The mobile device has an initial speed. The locating apparatus comprises a sensing unit, a calculation unit and a processing unit. The sensing unit is configured to sense acceleration information and height displacement information.

Abstract: An image warping method and a computer program product thereof are provided. The image warping method comprises the following steps: defining a plurality of original feature points of an original image, wherein the original image corresponds to an original view angle; calculating a plurality of original pixel coordinates of the original feature points in the original image; defining a plurality of new feature points of the original image, wherein the new feature points respectively correspond to the original feature points; calculating a plurality of new pixel coordinates of the new feature points projected onto the original image; and approaching each of the original pixel coordinates of the original feature points to each of the new pixel coordinates of the corresponding new feature points in the original image so that the original image is warped into a new image, wherein the new image corresponds to a new view angle.

Abstract: A three-dimensional image analysis system, a process device for use in the three-dimensional image analysis system, and a method thereof are provided. The three-dimensional image analysis system is configured to generate a plurality of three-dimensional data of a three-dimensional image. The process device defines a plurality of horizontal scan lines and a plurality of vertical scan lines according to the three dimensional data, determines a preliminary edge information of the three-dimensional image according to the horizontal scan lines and the vertical scan lines, divides the three dimensional data into a plurality of groups, compares the groups to determine a plane information of the three-dimensional image, and determines an edge information of the three-dimensional image according to the preliminary edge information and the plane information. The method is adapted for the process device.

Abstract: A building texture extracting apparatus and a method thereof are provided, wherein the building texture extracting apparatus comprises a storage unit and a processor. The storage unit is configured to store an aerial image and a panoramic image of a building. There is a coordinate correlation between the aerial image and the panoramic image.

Abstract: A position estimation system is provided, including at least one measurement unit, a plurality of evaluation units and a particle filter. The at least one measurement unit obtains a first information, wherein the first information at least includes a motion information and a corresponding noise model of a traced object. Each of the evaluation units has a corresponding evaluation model, wherein each evaluation model generates a corresponding unit displacement estimation according to the first information. The particle filter samples and generates a plurality of displacement estimations according to the unit displacement estimations and the corresponding noise models respectively.

Abstract: A locating apparatus, a locating method and a computer program storage product thereof for a mobile device are provided. The mobile device has an initial speed. The locating apparatus comprises a sensing unit, a calculation unit and a processing unit. The sensing unit is configured to sense acceleration information and height displacement information.

Abstract: A three-dimensional image analysis system, a process device for use in the three-dimensional image analysis system, and a method thereof are provided. The three-dimensional image analysis system is configured to generate a plurality of three-dimensional data of a three-dimensional image. The process device defines a plurality of horizontal scan lines and a plurality of vertical scan lines according to the three dimensional data, determines a preliminary edge information of the three-dimensional image according to the horizontal scan lines and the vertical scan lines, divides the three dimensional data into a plurality of groups, compares the groups to determine a plane information of the three-dimensional image, and determines an edge information of the three-dimensional image according to the preliminary edge information and the plane information. The method is adapted for the process device.

Abstract: A motion mode determination apparatus is disclosed, including an inertial device, a frequency decomposition module, a characteristic value generator, a training module and a determination module. The inertial device collects at least a first motion signal corresponding to a first motion mode and at least a second motion signal corresponding to a second motion mode, wherein each of the first and second motion signals includes a first signal, a second signal and a third signal. The frequency decomposition module decomposes the first signal into a first high-frequency signal and a first low-frequency signal. The characteristic value generator generates a plurality of characteristic values, wherein the characteristic values are the means and variances for each group of the first high-frequency signals, the first low-frequency signals, the second signals and the third signals respectively. The training module generates first and second data groups.