Feature extraction is a central step of processing Light Detection and Ranging (LIDAR) data. Existing detectors tend to exploit characteristics of specific environments: corners and lines from indoor (rectilinear) environments, and trees from outdoor environments. While these detectors work well in their intended environments, their performance in different environments can be poor. We describe...

In image retrieval, global features related to color or texture are commonly used to describe the image. The use of interest points in contentbased image retrieval allows image index to represent local properties of images. Classic corner detectors can be used for this purpose. However, they have drawbacks when applied to various natural images for image retrieval, because visual features need ...

In this homework, we use checker board pattern. We place the pattern on model plane(where Z component of world corrdinate is zero). And then several picture are taken by changing the location and rotation angle of the camera. We can get world coordinate of these corner easily by ordiering the corner point from top to bottom and from left to right. There are 8 vertical lines and 10 horizontal li...

Eyes play important roles in emotion and paralinguistic communications. Detection of eye state is necessaryfor applications such as driver awareness systems. In this paper, we develop an automatic system to detect eye-state action units (AU) based on Facial Action Coding System (FACS) by use of Gabor wavelets in a nearly frontal-viewed image sequence. Three eye-state AU (AU 41, AU42, and AU43) ...

A Fourier domain watermark localized near image feature points is presented in an attempt to make an invisible watermark that is robust to common image processing attacks. Finding robust feature points allows for localized watermarking to be detected after attacks. The feature points are found using the Harris corner detector. Points that respond greatest to the Harris corner detector will ofte...

In this paper, human facial expressions are recognized based on the mouth feature using Susan edge detector [3,4]. Face part is segmented from the face image, in which mouth feature is separated and potential geometrical features are used for the determination of facial expression such as surprise, neutral, sad and happy. Experimentation is done on standard JAFFE database [8] images of differen...

Image feature points are detected as pixels which locally maximize a detector function, two commonly used examples of which are the (Euclidean) image gradient and the Harris-Stephens corner detector. A major limitation of these feature detectors are that they are only Euclidean-invariant. In this work we demonstrate the application of a 2D affine-invariant image feature point detector based on ...

This paperoccursin the context of object recognition, and in particular, in the detection of 3D objects and their free forms by local descriptors of interest points to identify them. However, it remains to solve a several problems in this area that is related to the large amount of information and invariant to scale and angle of view. In this context, our purpose is to make the recognition of a...

This paper was made in the context of object recognition, and in particular, in the detection of 3D objects and their free forms by local descriptors of interest points to identify them. However, it remains to solve several problems in this area that is related to a large amount of information and invariant to scale and angle of view. In this context, our purpose is to make the recognition of a...