parser = argparse.ArgumentParser(description='Code for Feature Matching with FLANN tutorial.') parser.add_argument('--input1', help='Path to input image 1.', default ...
# Perform SIFT feature detection and description. sift = cv2.SIFT_create() kp0, des0 = sift.detectAndCompute(img0, None) kp1, des1 = sift.detectAndCompute(img1, None) # Define FLANN-based matching ...
Abstract: Visual servoing provides the flexibility of robot control in dynamic environments, but three-dimensional (3-D) robot visual servoing is challenging due to the 2-D nature of the image space.
Abstract: Homography estimation is crucial for image stitching in autonomous vehicle applications, enabling seamless multi-view transformations. While convolutional neural networks (CNNs) have ...