- Read more about ESTIMATION EFFICIENCY, ACCURACY AND ROBUSTNESS IMPROVEMENT BY EXPLOITING THE GEOMETRY INFORMATION IN RADAR MOVING TARGETS DETECTION AND IMAGING
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By exploiting the geometry information, the estimation performance (efficiency, accuracy and robustness) can be improved, and the conventional searching procedure can also be avoided. The concept of the methods can be used in the parameters estimation field, especially .
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- Read more about Detecting Occlusion from Color Information to Improve Visual Tracking - Presentation Slides
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Visual tracking in unconstrained environments often involves following an object that exhibits a number of appearance changes from factors such as scale change, rotation, and illumination. Effective tracking requires adapting a tracker to the object’s changing appearance over time. When a target becomes occluded by other objects in the scene, a naive tracker may end up learning the appearance of the occluding object. Our work introduces a method of detecting occlusion by considering the color profile of the target to prevent inappropriate tracker updates while the target is occluded.
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- Read more about Masked Correlation Filters for Partially Occluded Face Recognition
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- Read more about Discriminant Correlation Analysis for Feature Level Fusion with Application to Multimodal Biometrics
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In this paper, we present Discriminant Correlation Analysis (DCA), a feature level fusion technique that incorporates the class associations in correlation analysis of the feature sets. DCA performs an effective feature fusion by maximizing the pair-wise correlations across the two feature sets, and at the same time, eliminating the between-class correlations and restricting the correlations to be within classes.
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- Read more about Face Alignment by Deep Convolutional Network with Adaptive Learning Rate
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Deep convolutional network has been widely used in face recognition while not often used in face alignment. One of the most important reasons of this is the lack of training images annotated with landmarks due to fussy and time-consuming annotation work. To overcome this problem, we propose a novel data augmentation strategy. And we design an innovative training algorithm with adaptive learning rate for two iterative procedures, which helps the network to search an optimal solution.
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- Read more about CHUTE BASED AUTOMATED FISH LENGTH MEASUREMENT AND WATER DROP DETECTION
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Image processing and analysis techniques have drawn increasing attention since they enable a non-extractive and non-lethal approach to fisheries survey, such as fish size measurement, abundance prediction, catch estimation and compliance, species recognition and population counting. In this work, we present an innovative and effective method for measuring the chute-based fish length based on the morphological midline of the fish. The midline is generated through recursive morphological operations on the segmented fish mask.
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ICASSP 2016 presentation, Session: IVMP-P8 - Interpolation and Super-Resolution, Tursday, March 24, 13:30-15:30
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- Read more about A Data Set Providing Synthetic and Real-World Fisheye Video Sequences
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In video surveillance as well as automotive applications, so-called fisheye cameras are often employed to capture a very wide angle of view. To be able to develop and evaluate algorithms specifically adapted to fisheye images and videos, a corresponding test data set is therefore introduced in this paper. The sequences are freely available via www.lms.lnt.de/fisheyedataset/.
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