1. A method for classifying an object in a scene, comprising the steps of: preprocessing a sequence of images, wherein each image is acquired of the object in the scene by a scanner, wherein the scanner includes a 1D laser line sensor, and each image includes columns of pixels, and each pixel has an associated depth value such that each image is a range image, wherein the preprocessing further comprises; denoising each image in the sequence; removing background pixels from each image; projecting, in 3D, each image to a 3D world coordinate system; correcting depth values; extracting features; and classifying the sequence of images, wherein the classifying further comprises: applying an appearance classifier to the features to obtain labels; applying a sequence classifier to smooth the labels; and enforcing a structure of the object to determine a class of the object, wherein the steps are performed in a processor.
1. A method for classifying an object in a scene, comprising the steps of: preprocessing a sequence of images, wherein each image is acquired of the object in the scene by a scanner, wherein the scanner includes a 1D laser line sensor, and each image includes columns of pixels, and each pixel has an associated depth value such that each image is a range image, wherein the preprocessing further comprises; denoising each image in the sequence; removing background pixels from each image; projecting, in 3D, each image to a 3D world coordinate system; correcting depth values; extracting features; and classifying the sequence of images, wherein the classifying further comprises: applying an appearance classifier to the features to obtain labels; applying a sequence classifier to smooth the labels; and enforcing a structure of the object to determine a class of the object, wherein the steps are performed in a processor. 9. The method of claim 1 , wherein the scanner is mounted on a pole near the object.