Recognizing Articulated Objects Using Invariance

Recognizing articulated objects in SAR images

This paper presents the "rst sucessful approach for recognizing articulated vehicles in real synthetic aperture radar (SAR) images. This approach is based on invariant properties of the objects. Using SAR scattering center locations and magnitudes as features, the invariance of these features with articulation (e.g. turret rotation of a tank) is shown for XPATCH-generated synthetic SAR signatur...

Recognition of Articulated and Occluded Objects

ÐA model-based automatic target recognition (ATR) system is developed to recognize articulated and occluded objects in Synthetic Aperture Radar (SAR) images, based on invariant features of the objects. Characteristics of SAR target image scattering centers, azimuth variation, and articulation invariants are presented. The basic elements of the new recognition system are described and performanc...

Quasi-Invariants for Recognition of Articulated and Non-standard Objects in SAR Images

Using SAR scattering center locations and magnitudes as features, invariances with articulation (i.e., turret rotation for the ZSU 23/4 gun and T72 tank), with con guration variants (e.g. fuel barrels, searchlights, etc.) and with a depression angle change are shown for real SAR images obtained from the MSTAR public data. This location and magnitude quasi-invariance forms a basis for an innovat...

Methods for Recognizing Pose and Action of Articulated Objects with Collection of Planes in Motion

Stochastic Models for Recognition of Articulated Objects

In this paper, we present a hidden Markov modeling (HMM) based approach for recognition of articulated objects in synthetic aperture radar (SAR) images. W e develop multiple models for a given SAR image of an object and integrate these models synergistically using their probabilistic estimates for recognition and estimates of invariance of features as a result of articulation. The models are ba...