Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

Planning Algorithms: Introductory Material

3D shape is a crucial but heavily underutilized cue in today's computer vision systems, mostly due to the lack of a good generic shape representation. With the recent availability of inexpensive 2.5D depth sensors (e.g. Microsoft Kinect), it is becoming increasingly important to have a powerful 3D shape representation in the loop. Apart from category recognition, recovering full 3D shapes from view-based 2.5D depth maps is also a critical part of visual understanding. To this end, we propose to represent a geometric 3D shape as a probability distribution of binary variables on a 3D voxel grid, using a Convolutional Deep Belief Network. Our model, 3D ShapeNets, learns the distribution of complex 3D shapes across different object categories and arbitrary poses from raw CAD data, and discovers hierarchical compositional part representation automatically. It naturally supports joint object recognition and shape completion from 2.5D depth maps, and it enables active object recognition through view planning. To train our 3D deep learning model, we construct ModelNet - a large-scale 3D CAD model dataset. Extensive experiments show that our 3D deep representation enables significant performance improvement over the-state-of-the-arts in a variety of tasks.

/pdf/3d-shapenets-a-deep-representation-for-volumetric-shapes-1ii3phcu91.pdf

3D ShapeNets: A deep representation for volumetric shapes

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

http://cvssp-data.eps.surrey.ac.uk/Personal/AdrianHilton/Publications_files/survey_techrep.pdf

A survey of advances in vision-based human motion capture and analysis

Multisensor data fusion is an emerging technology applied to Department of Defense (DoD) areas such as automated target recognition, battlefield surveillance, and guidance and control of autonomous vehicles, and to non-DoD applications such as monitoring of complex machinery, medical diagnosis, and smart buildings. Techniques for multisensor data fusion are drawn from a wide range of areas including artificial intelligence, pattern recognition, statistical estimation and other areas. This paper provides a tutorial on data fusion, introducing data fusion applications, process models, and identification of applicable techniques. Comments are made on the state-of-the-art in data fusion.

An introduction to multisensor data fusion

This paper presents a tactical path planning algorithm for following ridges or valleys across a 3D terrain. The intent is to generate a path that enables an unmanned vehicle to surveil with maximum observability by traversing the ridges of a terrain or to operate with maximum covertness by navigating the valleys. The input to the algorithm is a 3D triangle mesh model for the terrain of interest. This mesh may be non-uniform and non-regular. Thus, the algorithm leverages research from computer graphics and computer vision to identify ridge-valley features on the terrain. These features serve as "obstacles" for an artificial potential field algorithm. The valleys are obstacles for a surveillance path, or the ridges are obstacles for a covert path. We incorporate geodesic-rather than Euclidean-distances into the potential field formulation to extend path planning to 3D surfaces. We present the theory of our proposed algorithm and provide experimental results

https://imaging.utk.edu/publications/papers/2006/ICRA06_dp.pdf

Ridge-valley path planning for 3D terrains

In the past few years, 3D face modeling has gained significant attention. Reliable modeling of the face is necessary for good performance of a 3D assisted face recognition system. In this paper, we model 3D human face from binocular stereo images. The stereo matching problem has been formulated as an energy minimization problem that progressively propagates depth from reliable regions to unreliable regions by an annealing scheme. The concept of smooth 2D grid is used to enable regularizing the final depth solution. In the energy equation, area based matching is used for the data term. The smoothness term relies on annealing. The 2D grid facilitates the estimation of the smoothness parameter, from a correlation profile obtained from neighborhood of the grid node. It is evident from 3D modeling results that the proposed algorithm performs well on images of human faces.

Stereo-based 3D Face Modeling using Annealing in Local Energy Minimization

The commercial face recognition software FaceIt® Identification and Surveillance was evaluated using the Facial Recognition Technology (FERET) database. The experimental results show the performance of FaceIt® with variations in illumination, expression, age, head size, pose, and the size of the database which all remain difficult problems in face recognition technology.

https://imaging.utk.edu/publications/papers/2003/heo_qcav03.pdf

Face recognition: evaluation report for FaceIt identification and surveillance

We present a new multiresolution analysis framework for irregular meshes with attributes based on the lifting scheme. We introduce a surface prediction operator to compute the detail coefficients for the geometry and the attributes of the model. Attribute analysis gives appearance information to complete the geometrical analysis of the model. A set of experimental results are given to show the efficiency of our framework. We present two applications to adaptive visualization and denoising.

Multiresolution analysis for meshes with appearance attributes

A new method is presented for the localization and recognition of three-dimensional objects using color information. In the first processing step, we estimate depth information by either applying a chromatic block matching method to color stereo images or acquiring a range image from a laser scanner. Second, the computed depth maps are segmented to distinguish between the image background and the objects that should be recognized. Assuming that the segmented regions represent single objects in the three-dimensional scene, feature vectors are generated based on color histograms. The Euclidean distance is used as well as the scalar product to measure the similarity between the feature vectors computed from the color image and the feature vectors stored in a database.

Mongi A. Abidi

Papers

Ridge-valley path planning for 3D terrains

Stereo-based 3D Face Modeling using Annealing in Local Energy Minimization

Face recognition: evaluation report for FaceIt identification and surveillance

Multiresolution analysis for meshes with appearance attributes

Finding objects in a 3D environment by combining distance measurement and color indexing