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2021
Effective assisted living environments must be able to perform inferences on how their occupants interact with their environment. Gaze direction provides strong indications of how people interact with their surroundings. In this paper, we propose a gaze tracking method that uses a neural network regressor to estimate gazes from keypoints and integrates
Paris Her +4 more
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Effective assisted living environments must be able to perform inferences on how their occupants interact with their environment. Gaze direction provides strong indications of how people interact with their surroundings. In this paper, we propose a gaze tracking method that uses a neural network regressor to estimate gazes from keypoints and integrates
Paris Her +4 more
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Constrained keypoint quantization
Proceedings of the 2nd ACM International Conference on Multimedia Retrieval, 2012Bag-of-words models are among the most widely used and successful representations in multimedia retrieval. However, the quantization error which is introduced when mapping keypoints to visual words is one of the main drawbacks of the bag-of-words model.
Yang Cai +3 more
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2020 25th International Conference on Pattern Recognition (ICPR), 2021
We propose a new hierarchical method to match keypoints by exploiting information across multiple scales. Traditionally, for each keypoint a single scale is detected and the matching process is done in the specific scale. We replace this approach with matching across scale-space.
Sina Lotfian, Hassan Foroosh
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We propose a new hierarchical method to match keypoints by exploiting information across multiple scales. Traditionally, for each keypoint a single scale is detected and the matching process is done in the specific scale. We replace this approach with matching across scale-space.
Sina Lotfian, Hassan Foroosh
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2019 International Conference on Document Analysis and Recognition Workshops (ICDARW), 2019
In keypoint regression, models are trained to consume an image and produce the x, y coordinates of some entity, e.g., a person's nose or corner of a document. Typical methods for doing so include linear regression over deep features to directly produce x, y coordinates and training networks to regress a dense heatmap around each keypoint.
Christopher Tensmeyer, Tony Martinez
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In keypoint regression, models are trained to consume an image and produce the x, y coordinates of some entity, e.g., a person's nose or corner of a document. Typical methods for doing so include linear regression over deep features to directly produce x, y coordinates and training networks to regress a dense heatmap around each keypoint.
Christopher Tensmeyer, Tony Martinez
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Detecting Keypoints for Automated Annotation of Bounding Boxes using Keypoint Extraction
2020 International Conference on Computational Science and Computational Intelligence (CSCI), 2020Object detection requires an enormous amount of training data annotated by bounding boxes. All bounding boxes are manually drawn, which leads to highly expensive labor costs. Therefore, this study proposes automatic bounding box annotation of training data for object detection.
Kaito Ishizaki +2 more
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Complementary Keypoint Descriptors
2016We examine the use of complementary descriptors for keypoint recognition in digital images. The descriptors combine multiple types of information, including shape, color, and texture. We first review several keypoint descriptors and propose new descriptors that use normalized brightness/color spatial histograms.
Clark F. Olson +3 more
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Scale-invariant corner keypoints
2014 IEEE International Conference on Image Processing (ICIP), 2014Effective and efficient generation of keypoints from images is the first step of many computer vision applications, such as object matching. The last decade presented us with an arms race toward faster and more robust keypoint detection, feature description and matching.
Bo Li, Haibo Li, Ulrik Soderstrom
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Keypoint-Based Keyframe Selection
IEEE Transactions on Circuits and Systems for Video Technology, 2013Keyframe selection has been crucial for effective and efficient video content analysis. While most of the existing approaches represent individual frames with global features, we, for the first time, propose a keypoint-based framework to address the keyframe selection problem so that local features can be employed in selecting keyframes.
Genliang Guan +4 more
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Multi-scale Local Implicit Keypoint Descriptor for Keypoint Matching
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023JongMin Lee, Eunhyeok Park, Sungjoo Yoo
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Detect Any Keypoints: An Efficient Light-Weight Few-Shot Keypoint Detector
Proceedings of the AAAI Conference on Artificial IntelligenceRecently the prompt-based models have become popular across various language and vision tasks. Following that trend, we perform few-shot keypoint detection (FSKD) by detecting any keypoints in a query image, given the prompts formed by support images and keypoints. FSKD can be applied to detecting keypoints and poses of diverse animal species. In order
Changsheng Lu, Piotr Koniusz
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