Abstract: Methods of forming line-end extensions and devices having line-end extensions are provided. In some embodiments, a method includes forming a patterned photoresist on a first region of a hard mask layer. A line-end extension region is formed in the hard mask layer. The line-end extension region extends laterally outward from an end of the first region of the hard mask layer. The line-end extension region may be formed by changing a physical property of the hard mask layer at the line-end extension region.

Abstract: A surface adaptation method suitable for a vehicle includes evaluating a plurality of longitudinal forces with respect to a plurality of sampling points, evaluating a plurality of wheel slips with respect to the plurality of sampling points, determining a maximum longitudinal force from the plurality of longitudinal forces, and determining a wheel slip threshold from the plurality of wheel slips. The wheel slip threshold corresponds to the maximum longitudinal force.

Abstract: An image adaptive feature extraction method includes dividing an image into a plurality of blocks, performing a feature extraction processing on the plurality of blocks, and obtaining a block feature from each of the plurality of blocks after the feature extraction processing; calculating each block feature by means of a support vector machine (SVM) classifier, wherein each block feature is calculated to obtain a hyperplane normal vector; setting a threshold value, determining the block feature according to the hyperplane normal vector, recording the block as an adaptive feature block when a value of the hyperplane normal vector is higher than the threshold value, and integrating each adaptive feature block to form an adaptive feature image. Because an image adaptive feature extraction process is performed before a pedestrian image detection is calculated, and effective feature data is then selected, computational efficiency is boosted and detection pedestrian error probability is reduced.

Abstract: A surface adaptation method suitable for a vehicle includes evaluating a plurality of longitudinal forces with respect to a plurality of sampling points, evaluating a plurality of wheel slips with respect to the plurality of sampling points, determining a maximum longitudinal force from the plurality of longitudinal forces, and determining a wheel slip threshold from the plurality of wheel slips. The wheel slip threshold corresponds to the maximum longitudinal force.

Abstract: A light detection and ranging system comprises an optical transmitter for beam scanning on a scan region, and receiving reflected light from the scan region; and an optical receiver for directing the reflected light for signal conversion. The optical transmitter includes a beam refractive unit including optical refractive devices, rotatably disposed about a rotation axis, for directing a collimated laser beam from a first optical path towards a direction depending on rotation angles of the optical refractive devices; and a motion unit for actuating relative motion of the optical refractive devices so as to perform beam scanning towards directions on the scan region. The optical receiver includes an off-axis reflective unit, disposed in the first optical path, for directing the reflected light towards a second optical path; and a light detection unit, disposed in the second optical path, for performing signal conversion on the reflected light.

Abstract: A method for performing pedestrian detection with aid of light detection and ranging (LIDAR) is provided. The method includes: obtaining 3-dimensional (3D) point cloud data through the LIDAR; performing ground separation processing on the 3D point cloud data to remove ground information; performing object extraction processing on the 3D point cloud data to obtain 3D point cloud chart that includes pedestrian candidate point cloud group; performing 2-dimensional (2D) mapping processing on the 3D point cloud chart to obtain 2D chart; and extracting 3D feature and 2D feature from the 3D point cloud chart and the 2D chart, respectively, and utilizing the 3D feature and the 2D feature to determine location of the pedestrian. According to the method, image data obtained by the LIDAR may be enhanced, the method may distinguish between pedestrian far away and environment blocks, and pedestrian recognition in nighttime or in bad weather may be improved.

Abstract: A vehicle detection method includes acquiring a three-dimensional (3D) image with a plurality of point clouds; mapping the 3D image onto a two-dimensional (2D) image; interpolating the 2D image according to a distance between a camera and a first point cloud of the plurality of point clouds; transforming the 3D image into a plurality of voxels, and extracting a plurality of 3D deep features and a plurality of 2D deep features according to the plurality of voxels; and determining a detection result according to a classification of the plurality of 3D deep features and the plurality of 2D deep features.

Abstract: An image adaptive feature extraction method includes dividing an image into a plurality of blocks, performing a feature extraction processing on the plurality of blocks, and obtaining a block feature from each of the plurality of blocks after the feature extraction processing; calculating each block feature by means of a support vector machine (SVM) classifier, wherein each block feature is calculated to obtain a hyperplane normal vector; setting a threshold value, determining the block feature according to the hyperplane normal vector, recording the block as an adaptive feature block when a value of the hyperplane normal vector is higher than the threshold value, and integrating each adaptive feature block to form an adaptive feature image. Because an image adaptive feature extraction process is performed before a pedestrian image detection is calculated, and effective feature data is then selected, computational efficiency is boosted and detection pedestrian error probability is reduced.

Abstract: A method for extracting features of a thermal image is provided. The method includes: reading a thermal image, and dividing the thermal image into a plurality of block images; and extracting a histogram of oriented gradient (HOG) feature histogram from each of the plurality of block images, and transforming the HOG feature histogram of each of the plurality of block images into a symmetric weighting HOG (SW-HOG) feature histogram. The SW-HOG feature histogram is obtained by multiplying a histogram of gradient intensity distribution by a block weighting. The method increases weightings of blocks which cover human contours and reduces weightings of blocks of an internal region of a human appearance through analyzing thermal lightness difference of regions within blocks, to reduce the influence of clothes in the internal region and the influence of the background region.

Abstract: A laser radar device comprises a laser projecting system and a laser radar detecting system. The laser projecting system comprises a laser diode; and a light source orientation adjustment unit comprising a collimating lens and a Powell lens to modulate the angle at which the first incident laser beam is projected onto an object. The laser radar detecting system comprises at least two laser radar detection units disposed in the horizontal direction and vertical direction of the object, respectively. The laser radar detection units each comprise a wedge-shaped lens, an aspherical lens system and an optical detector. By designing optical parameters of the wedge-shaped lens and stacking the laser radar detection units in the horizontal direction and vertical direction, it is feasible to facilitate overall device manufacturing and processing, meet R&D needs, and adjust an optical system in its entirety easily.

Abstract: A method for performing pedestrian detection with aid of light detection and ranging (LIDAR) is provided. The method includes: obtaining 3-dimensional (3D) point cloud data through the LIDAR; performing ground separation processing on the 3D point cloud data to remove ground information; performing object extraction processing on the 3D point cloud data to obtain 3D point cloud chart that includes pedestrian candidate point cloud group; performing 2-dimensional (2D) mapping processing on the 3D point cloud chart to obtain 2D chart; and extracting 3D feature and 2D feature from the 3D point cloud chart and the 2D chart, respectively, and utilizing the 3D feature and the 2D feature to determine location of the pedestrian. According to the method, image data obtained by the LIDAR may be enhanced, the method may distinguish between pedestrian far away and environment blocks, and pedestrian recognition in nighttime or in bad weather may be improved.

Abstract: A method for extracting features of a thermal image is provided. The method includes: reading a thermal image, and dividing the thermal image into a plurality of block images; and extracting a histogram of oriented gradient (HOG) feature histogram from each of the plurality of block images, and transforming the HOG feature histogram of each of the plurality of block images into a symmetric weighting HOG (SW-HOG) feature histogram. The SW-HOG feature histogram is obtained by multiplying a histogram of gradient intensity distribution by a block weighting. The method increases weightings of blocks which cover human contours and reduces weightings of blocks of an internal region of a human appearance through analyzing thermal lightness difference of regions within blocks, to reduce the influence of clothes in the internal region and the influence of the background region.

Abstract: A light detection and ranging system comprises an optical transmitter for beam scanning on a scan region, and receiving reflected light from the scan region; and an optical receiver for directing the reflected light for signal conversion. The optical transmitter includes a beam refractive unit including optical refractive devices, rotatably disposed about a rotation axis, for directing a collimated laser beam from a first optical path towards a direction depending on rotation angles of the optical refractive devices; and a motion unit for actuating relative motion of the optical refractive devices so as to perform beam scanning towards directions on the scan region. The optical receiver includes an off-axis reflective unit, disposed in the first optical path, for directing the reflected light towards a second optical path; and a light detection unit, disposed in the second optical path, for performing signal conversion on the reflected light.

Abstract: A laser radar system capable of active polarization comprises a signal processing unit for sending a control signal; a laser emitting unit for emitting a first laser to a target after receiving the control signal, wherein the laser emitting unit comprises a liquid crystal polarization driver and a liquid crystal polarization component group, and the liquid crystal polarization driver controls a phase delay of the liquid crystal polarization component group to therefore change a polarized state of the first laser; and a laser receiving unit for receiving a second laser reflected off the target and analyzing polarization information of the second laser through the signal processing unit to evaluate surface characteristics of the target.

Abstract: An all-weather thermal-image pedestrian detection method includes (a) capturing diurnal thermal images and nocturnal thermal images of a same pedestrian and non-pedestrian object in a same defined block to create a sample database of thermal images, wherein the sample database comprises pedestrian samples and non-pedestrian samples; (b) performing LBP encoding on the pedestrian samples and the non-pedestrian samples, wherein complementary LBP codes in the same defined block are treated as identical LBP codes; (c) expressing the LBP codes in the same defined block as features by a gradient direction histogram (HOG) to obtain feature training samples of the pedestrian samples and the non-pedestrian samples; (d) entering the feature training samples into a SVM to undergo training by Adaboost so as to form a strong classifier; and (e) effectuating pedestrian detection by searching the strong classifiers in thermal images with sliding window technique to detect for presence of pedestrians.

Abstract: A laser radar system capable of active polarization comprises a signal processing unit for sending a control signal; a laser emitting unit for emitting a first laser to a target after receiving the control signal, wherein the laser emitting unit comprises a liquid crystal polarization driver and a liquid crystal polarization component group, and the liquid crystal polarization driver controls a phase delay of the liquid crystal polarization component group to therefore change a polarized state of the first laser; and a laser receiving unit for receiving a second laser reflected off the target and analyzing polarization information of the second laser through the signal processing unit to evaluate surface characteristics of the target.

Abstract: A laser radar device comprises a laser projecting system and a laser radar detecting system. The laser projecting system comprises a laser diode; and a light source orientation adjustment unit comprising a collimating lens and a Powell lens to modulate the angle at which the first incident laser beam is projected onto an object. The laser radar detecting system comprises at least two laser radar detection units disposed in the horizontal direction and vertical direction of the object, respectively. The laser radar detection units each comprise a wedge-shaped lens, an aspherical lens system and an optical detector. By designing optical parameters of the wedge-shaped lens and stacking the laser radar detection units in the horizontal direction and vertical direction, it is feasible to facilitate overall device manufacturing and processing, meet R&D needs, and adjust an optical system in its entirety easily.

Abstract: An all-weather thermal-image pedestrian detection method includes (a) capturing diurnal thermal images and nocturnal thermal images of a same pedestrian and non-pedestrian object in a same defined block to create a sample database of thermal images, wherein the sample database comprises pedestrian samples and non-pedestrian samples; (b) performing LBP encoding on the pedestrian samples and the non-pedestrian samples, wherein complementary LBP codes in the same defined block are treated as identical LBP codes; (c) expressing the LBP codes in the same defined block as features by a gradient direction histogram (HOG) to obtain feature training samples of the pedestrian samples and the non-pedestrian samples; (d) entering the feature training samples into a SVM to undergo training by Adaboost so as to form a strong classifier; and (e) effectuating pedestrian detection by searching the strong classifiers in thermal images with sliding window technique to detect for presence of pedestrians.