Szeliski, Richard 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]. Cited in 5 Documents 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:TrackFormer; Vid2Curve; MVSNet; ESPNet; DVDnet; BMBC; NeuralFusion; ViLBERT; IBRNet; HyperNeRF; PatchmatchNet; PVNet; DeepHandMesh; LabelMe; Pfinder; D2D; VPLNet; Pixel2Mesh; Vid2Player; EfficientDet; NeuS; UCF101; MLESAC; OpenSesame; WxBS; Open3D; YOLO; Halide; DeepFace; HeadOn; PyTorch; Qsplat; ImageNet; cleverhans; FBNetV2; XNOR-Net; Inception-v4; StyleGAN2; GRAB; PIFu; SuperGlue; MobileNetV2; SOSNet; OpenGL; MeshSDF; R2D2; InLoc; AutoDispNet; SurfelMeshing; EPINET; DeepVoxels; ResMLP; AutoFlow; FastDVDnet; SMD-Nets; Objects365; StructureFlow; FrankMocap; MetaSDF; MOTS; EdgeStereo; Vid2Actor; NeRV; FaceNet; Theia; RoutedFusion; L2-Net; MLP-Mixer; NeX; CvT; DeepPruner; SuperPoint; MS-COCO; BERT; FlowNet; iSAM2; MMDetection; ShapeNet; KITTI; DARTS; VQA; SoftPOSIT; SSD; SMPL; DenseCap; ArcFace; mixup; CityPersons; RetinaFace; DensePose; ShuffleNet; CIDEr; StarGAN; ASLFeat; InfoGAN; ContextDesc; WSABIE; S4L; Adam; DeblurGAN; Colorization Transformer; Swin Transformer; COTR; Make3D; D2-Net; VIBE; ViDeNN; Megaman; ViViT; MAGSAC++; RecResNet; StereoDRNet; BundleFusion; GANSpace; PoseCNN; GANFIT; FrameNet; DeepMVS; PointVoteNet; MirrorFlow; Pixel-BERT; S2DNet; Motion2fusion; MatryODShka; MonoSLAM; DeCAF; RelocNet; PatchMatch; SegFlow; Caffe; LiteFlowNet3; FastNeRF; GrokNet; Rouge; OpenCV; DeepLab; ORB-SLAM; DTAM; KinectFusion; COIL-100; Im2Text; openMVG; DeepSDF; ORB-SLAM2; BLEU; pixelNeRF; SynSin; NeurVPS; MuCAN; HyperDepth; GeoS; DeepMedic; GSLAM; PhySG; WildDash; PlenOctrees; OpenGV; AdaCoF; SEAGULL; GeoDesc; Unselfie; VNect; TransGAN; BiT; TextureFusion; ShadowDraw; StackGAN; LiveCap; 3DLite; UltraStereo; FusionSeg; StereoNet; StructSLAM; PPGNet; NeRF++; DualGAN; Oscar; Omnimatte; SBA; PIFuHD; MNIST; AnchorNet; SegStereo; revolve; PointNet; SinGAN; KiloNeRF; LoFTR; Patch2Pix; VideoBERT; LAPACK; NeRF; CamNet; Soft scissors; HPatches; Key.Net; OpenPose; Flickr30K; SqueezeNet; Face2Face; Fashion-MNIST; BRISK; PWC-Net; ClusterFit; EfficientNet; DISN; NIMA; MeshLab PDFBibTeX XMLCite \textit{R. Szeliski}, Computer vision. Algorithms and applications. 2nd edition. Cham: Springer (2022; Zbl 1478.68007) Full Text: DOI