Lunar Terrain and Albedo Reconstruction from Apollo Imagery

Generating accurate three dimensional planetary models and albedo maps is becoming increasingly more important as NASA plans more robotics missions to the Moon in the coming years. This paper describes a novel approach for separation of topography and albedo maps from orbital Lunar images. Our method uses an optimal Bayesian correlator to refine the stereo disparity map and generate a set of accurate digital elevation models (DEM). The albedo maps are obtained using a multi-image formation model that relies on the derived DEMs and the Lunar- Lambert reflectance model. The method is demonstrated on a set of high resolution scanned images from the Apollo era missions

Photometric Lunar Surface Reconstruction

Accurate photometric reconstruction of the Lunar surface is important in the context of upcoming NASA robotic missions to the Moon and in giving a more accurate understanding of the Lunar soil composition. This paper describes a novel approach for joint estimation of Lunar albedo, camera exposure time, and photometric parameters that utilizes an accurate Lunar-Lambertian reflectance model and previously derived Lunar topography of the area visualized during the Apollo missions. The method introduced here is used in creating the largest Lunar albedo map (16% of the Lunar surface) at the resolution of 10 meters/pixel

Hidden Markov Models For Face Recognition

The work presented in this paper focuses on the use of Hidden Markov Models for face recognition. A new method based on the extraction of 2D-DCT feature vectors is described, and the recognition results are compared with other face recognition approaches. The method introduced in this paper reduces significantly the computational complexity of previous HMM-based face recognition system, while preserving the same recognition rate. 1. INTRODUCTION Face recognition from still images and video sequences is emerging as an active research area with numerous commercial and law enforcement applications. These applications require robust algorithms for human face recognition under different lighting conditions, facial expressions, and orientations. An excellent survey on face recognition is given in [1]. Previous attempts to develop a face recognition system that has a high recognition rate include the correlation method [2], the eigenface method [3] and the linear discriminant method [4]. Howe..

A Hidden Markov Model-Based Approach for Face Detection and Recognition

Contents 1 Introduction 1 2 Related Work 4 2.1 Correlation Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Karhunen-Loeve Expansion - Based Methods . . . . . . . . . . . . . . . . . 5 2.2.1 Recognition Using Eigenfaces . . . . . . . . . . . . . . . . . . . . . . 5 2.2.2 The "Parametric" Approach versus the "View-Based" Approach . . 6 2.2.3 Recognition Using Eigenfeatures . . . . . . . . . . . . . . . . . . . . 6 2.3 Linear Discriminant Methods - Fisherfaces . . . . . . . . . . . . . . . . . . . 7 2.4 Singular Value Decomposition Methods . . . . . . . . . . . . . . . . . . . . 7 2.5 Hidden Markov Model Based Methods . . . . . . . . . . . . . . . . . . . . . 8 2.6 Summary of the Related Work . . . . . . . . . . . . . . . . . . . . . . . . . 11 3 The Proposed Approach 13 3.1 A rule based approach for head detection . . . . . . . . . . . . . . . . . . . 13 3.2 Human Face Modeling using Hidden Markov Models . . . . . . . . . . .

Photometric Recovery of Ortho-Images Derived from Apollo 15 Metric Camera Imagery

Abstract. The topographical and photometric reconstruction of the moon from Apollo metric data has gained attention to support manned mission planning since the NASA has been working on return to the moon in 2004. This paper focuses on photometric recovery of the moon surface from Apollo orbital imagery. The statistical behavior of photons generates the scene radiance which follows a continuous Poisson distribution with the mean of surface radiance. The pixel value is determined by the camera response of sensor exposure which is proportional to scene radiance and exposure time. The surface radiance, exposure time and camera response are estimated by the maximum likelihood method for sensor exposure. The likelihood function is highly nonlinear and we were unable to find an estimator in closed form. Grouping the three sets of parameters (surface radiance, exposure time, and camera response), an EM-like juggling algorithm is proposed to determine the one family of parameters from the others. The photometric recovery of otho-images derived from Apollo 15 metric camera imagery was presented to show the validity of the proposed method. 1

Real-Time Detection of Human Faces in Uncontrolled Environments

This paper presents an approach for the detection of human face and eyes in real time and in uncontrolled environments. The system has been implemented on a PC platform with the aid of simple commercial devices such as an NTSC video camera and a monochrome frame grabber. The approach is based on a probabilistic framework that uses a deformable template model to describe the human face. The system has been tested on both head-and-shoulder sequences as well as complex scenes with multiple people and random motion. The system is able to locate the eyes from different head poses (rotations in image plane as well as in depth). The information provided by the location of the eyes is used to extract faces with frontal pose from a video sequence. The extracted frontal frames can be passed to recognition and classification systems for further processing. Keywords : Face Detection, Eye Detection, Face Segmentation, Ellipse Fitting 1. INTRODUCTION In recent years, face detection from video data ..

A Multi-Stream Audio-Video Large-Vocabulary Mandarin Chinese Speech Database

In this paper we present the acquisition and content of a multi-stream audio-visual large-vocabulary database in Mandarin Chinese. The database consists of 17,000 utterances spoken by 225 people and captured by a set of seven cameras and 12 microphones. We also provide the label files that describe the end points of the utterances and the script files that represent the actual pronunciation of speech. The database introduced in this paper is can be used in audio-visual speech recognition (AVSR) for both largevocabulary and small tasks, microphone array based speech recognition, audio-visual speaker identification and 3D face modeling. 1