Silhouette-Based Action Recognition Using Simple Shape Descriptors

2018 ◽  
pp. 413-424 ◽  
Author(s):  
Katarzyna Gościewska ◽  
Dariusz Frejlichowski
Keyword(s):  
Action Recognition ◽  
Shape Descriptors ◽  
Simple Shape

scholarly journals VOLUME ESTIMATION FROM SINGLE IMAGES: AN APPLICATION TO PANCREATIC ISLETS

2018 ◽  
Vol 37 (3) ◽  
pp. 191 ◽  
Author(s):  
Jiří Dvořák ◽  
Jan Švihlík ◽  
Jan Kybic ◽  
Barbora Radochová ◽  
Jiří Janáček ◽  
...  
Keyword(s):  
Volume Estimation ◽  
Estimation Methods ◽  
Particle Model ◽  
Shape Descriptors ◽  
Single Image ◽  
Simple Shape ◽  
Segmented Image ◽  
Image Volume ◽  
3D Shapes ◽  
Better Than

The present paper deals with the problem of volume estimation of individual objects from a single 2D view. Our main application is volume estimation of pancreatic (Langerhans) islets and the single 2D view constraint comes from the time and equipment limitations of the standard clinical procedure.Two main approaches are followed in this paper. First, two regression-based methods are proposed, using a set of simple shape descriptors of the segmented image of the islet. Second, two example-based methods are proposed, based on a database of islets with known volume. For training and evaluation, islet volumes were determined by OPT microscopy and a semi-automatical stereological volume estimation using the so-called Fakir probes.The performance of the single image volume estimation methods is studied on a set of 99 islets from human donors. Further experiments were also performed on a stone dataset and on synthetic 3D shapes, generated using a flexible stochastic particle model. The proposed methods are fast and the experimental results show that in most situations the proposed methods perform significantly better than the methods currently used in clinical practice, which are based on simple spherical or ellipsoidal models.

scholarly journals The Analysis of Shape Features for the Purpose of Exercise Types Classification Using Silhouette Sequences

2020 ◽  
Vol 10 (19) ◽  
pp. 6728 ◽  
Author(s):  
Katarzyna Gościewska ◽  
Dariusz Frejlichowski
Keyword(s):  
Action Recognition ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Recognition System ◽  
Activity Levels ◽  
Shape Features ◽  
Simple Shape ◽  
Action Sequence ◽  
Single Person ◽  
Shape Characteristics

This paper presents the idea of using simple shape features for action recognition based on binary silhouettes. Shape features are analysed as they change over time within an action sequence. It is shown that basic shape characteristics can discriminate between short, primitive actions performed by a single person. The proposed approach is tested on the Weizmann database using a various number of classes. Binary foreground masks (silhouettes) are replaced with convex hulls, which highlights some shape characteristics. Centroid locations are combined with some other simple shape descriptors. Each action sequence is represented using a vector with shape features and Discrete Fourier Transform. Classification is based on leave-one-sequence-out approach and employs Euclidean distance, correlation coefficient or C1 correlation. A list of processing steps for action recognition is explained and followed by some experiments that yielded accuracy exceeding 90%. The idea behind the presented approach is to develop a solution for action recognition that could be applied in a kind of human activity recognition system associated with the Ambient Assisted Living concept, helping adults increasing their activity levels by monitoring them during exercises.

Interpretation of the Filament Depression at Millimetric and Centimetric Wavelengths

1979 ◽  
Vol 44 ◽  
pp. 131-134
Author(s):  
A. Raoult ◽  
P. Lantos ◽  
E. Fürst
Keyword(s):  
Radio Telescope ◽  
Active Regions ◽  
Simple Shape ◽  
Quiet Sun ◽  
Unstable Process

The depressions at centimetric and millimetric wavelengths associated with the filaments are studied using already published maps as well as unpublished observations from the Effelsberg 100 m radio telescope of the M.P.I., Bonn. The study has been restricted to large Ha quiescent prominences of relatively simple shape, situated far from the limb and from active regions. The data has been reduced employing one method whose main characteristics are choice of a local quiet sun definition and avoidance of the unstable process of deconvolution.

Human action recognition using simple geometric features and a finite state machine

2013 ◽  
Vol 18 (2-3) ◽  
pp. 49-60 ◽  
Author(s):  
Damian Dudzńiski ◽  
Tomasz Kryjak ◽  
Zbigniew Mikrut
Keyword(s):  
Action Recognition ◽  
Finite State Machine ◽  
Recognition Rate ◽  
Human Action Recognition ◽  
Human Action ◽  
Video Stream ◽  
State Machine ◽  
Recognition Algorithm ◽  
Finite State ◽  
Correct Recognition Rate

Abstract In this paper a human action recognition algorithm, which uses background generation with shadow elimination, silhouette description based on simple geometrical features and a finite state machine for recognizing particular actions is described. The performed tests indicate that this approach obtains a 81 % correct recognition rate allowing real-time image processing of a 360 X 288 video stream.

Deep Learning for Human Action Recognition Survey

2018 ◽  
Vol 6 (10) ◽  
pp. 323-328
Author(s):  
K.Kiruba . ◽  
D. Shiloah Elizabeth ◽  
C Sunil Retmin Raj
Keyword(s):  
Deep Learning ◽  
Action Recognition ◽  
Human Action Recognition ◽  
Human Action
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