[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Zhao et al., 2021 - Google Patents

Tsdm: Tracking by siamrpn++ with a depth-refiner and a mask-generator

Zhao et al., 2021

View PDF
Document ID
13561259379611507847
Author
Zhao P
Liu Q
Wang W
Guo Q
Publication year
Publication venue
2020 25th International conference on pattern recognition (ICPR)

External Links

Snippet

In a generic object tracking, depth (D) information provides informative cues for foreground- background separation and target bounding box regression. However, so far, few trackers have used depth information to play the important role aforementioned due to the lack of a …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00268—Feature extraction; Face representation
    • G06K9/00281—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30781—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F17/30784—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre
    • G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing

Similar Documents

Publication Publication Date Title
Zhang et al. An object tracking framework with recapture based on correlation filters and Siamese networks
Von Stumberg et al. Gn-net: The gauss-newton loss for multi-weather relocalization
Zhao et al. Tsdm: Tracking by siamrpn++ with a depth-refiner and a mask-generator
Sun et al. Correlation tracking via joint discrimination and reliability learning
Fischer et al. Flownet: Learning optical flow with convolutional networks
Yang et al. Every pixel counts: Unsupervised geometry learning with holistic 3d motion understanding
Kart et al. How to make an rgbd tracker?
Borji et al. Adaptive object tracking by learning background context
Lu et al. Human action segmentation with hierarchical supervoxel consistency
Spina et al. Hybrid approaches for interactive image segmentation using the live markers paradigm
US8238650B2 (en) Adaptive scene dependent filters in online learning environments
Yu et al. Robust thermal infrared object tracking with continuous correlation filters and adaptive feature fusion
García et al. Adaptive multi-cue 3D tracking of arbitrary objects
CN103955950B (en) Image tracking method utilizing key point feature matching
Yuan et al. Self-supervised object tracking with cycle-consistent siamese networks
Zheng et al. Self-supervised monocular depth estimation based on combining convolution and multilayer perceptron
Fu et al. Distractor-aware event-based tracking
Zeng et al. Towards discriminative representations with contrastive instances for real-time uav tracking
Petrovai et al. Semi-automatic image annotation of street scenes
Li et al. SiamPolar: Semi-supervised realtime video object segmentation with polar representation
Pan et al. SiamCA: Siamese visual tracking with customized anchor and target-aware interaction
Gong et al. Visual tracking with pyramidal feature fusion and transformer based model predictor
Ghafarianzadeh et al. Efficient, dense, object-based segmentation from RGBD video
Fan et al. SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Estimation
Yuan et al. Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds