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Computer vision. Algorithms and applications. 2nd edition. (English) Zbl 1478.68007

Texts in Computer Science. Cham: Springer (ISBN 978-3-030-34371-2/hbk; 978-3-030-34374-3/pbk; 978-3-030-34372-9/ebook). xxii, 925 p. (2022).
Publisher’s description: Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos.
More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles.
Topics and features:
Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses
ncorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality
Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects
Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade
Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software
Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
See the review of the first edition in [Zbl 1219.68009].

MSC:

68-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science
68T07 Artificial neural networks and deep learning
68T45 Machine vision and scene understanding
68U05 Computer graphics; computational geometry (digital and algorithmic aspects)
68U10 Computing methodologies for image processing
68-04 Software, source code, etc. for problems pertaining to computer science

Citations:

Zbl 1219.68009

Software:

ORB-SLAM2; BLEU; PointVoteNet; Im2Text; PoseCNN; D2-Net; ASLFeat; StarGAN; Rouge; Pixel-BERT; FastNeRF; BiT; 3DLite; ShadowDraw; SegFlow; BRISK; Unselfie; SoftPOSIT; DeepMedic; StructSLAM; OpenPose; SMPL; ShuffleNet; CamNet; GSLAM; PhySG; PlenOctrees; PIFuHD; SSD; AdaCoF; DensePose; S2DNet; DTAM; MatryODShka; Make3D; DeCAF; Caffe; MonoSLAM; Megaman; KinectFusion; COIL-100; openMVG; GrokNet; revolve; DeepMVS; DeepLab; GANFIT; Adam; DeepSDF; Swin Transformer; ORB-SLAM; InfoGAN; MirrorFlow; COTR; ContextDesc; LiteFlowNet3; GANSpace; EfficientDet; Patch2Pix; SynSin; UltraStereo; FrameNet; GeoS; StereoNet; LoFTR; WSABIE; NeurVPS; NeRF++; pixelNeRF; ViViT; KiloNeRF; SinGAN; CIDEr; SEAGULL; DARTS; TransGAN; DeepPruner; mixup; LiveCap; PPGNet; Colorization Transformer; LAPACK; DualGAN; MAGSAC++; WildDash; Omnimatte; VQA; HyperDepth; FusionSeg; OpenGV; ShapeNet; Oscar; NIMA; GeoDesc; ArcFace; VNect; SuperPoint; RetinaFace; Motion2fusion; Key.Net; HPatches; iSAM2; ViLBERT; S4L; FlowNet; ClusterFit; NeRF; DeblurGAN; RecResNet; StereoDRNet; Face2Face; BERT; SBA; SqueezeNet; MMDetection; ViDeNN; Flickr30K; PWC-Net; Soft scissors; MS-COCO; SegStereo; RelocNet; BundleFusion; VIBE; KITTI; MNIST; AnchorNet; OpenCV; Fashion-MNIST; EfficientNet; DenseCap; TextureFusion; PatchMatch; MuCAN; PointNet; StackGAN; VideoBERT; CityPersons; LabelMe; UCF101; YOLO; MLESAC; OpenSesame; Pixel2Mesh; Open3D; FaceNet; Halide; DeepFace; PyTorch; cleverhans; ImageNet; Qsplat; Inception-v4; XNOR-Net; MobileNetV2; DVDnet; Vid2Player; CvT; NeX; Vid2Actor; NeuralFusion; RoutedFusion; VPLNet; Vid2Curve; PatchmatchNet; SMD-Nets; MLP-Mixer; SOSNet; D2D; HeadOn; FastDVDnet; IBRNet; NeuS; L2-Net; Theia; EPINET; R2D2; AutoFlow; NeRV; EdgeStereo; DeepVoxels; MetaSDF; Objects365; AutoDispNet; FrankMocap; StructureFlow; MeshSDF; SurfelMeshing; FBNetV2; MVSNet; PIFu; InLoc; SuperGlue; GRAB; ESPNet; TrackFormer; WxBS; OpenGL; DeepHandMesh; BMBC; HyperNeRF; PVNet; ResMLP; DISN; Pfinder; MeshLab; StyleGAN2; MOTS
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