scholarly journals Shadow Penumbras for Complex Objects by Depth-Dependent Filtering of Multi-Layer Depth Images

1999 ◽  
pp. 197-212 ◽  
Author(s):  
Brett Keating ◽  
Nelson Max
Keyword(s):  
Layer Depth ◽  
Complex Objects ◽  
Depth Images

scholarly journals Simulation of Motion Parallax for Monitor-Based Augmented Reality Applications

2013 ◽  
Author(s):  
Rafael Radkowski ◽  
James Oliver
Keyword(s):  
Augmented Reality ◽  
Motion Parallax ◽  
Video Camera ◽  
Head Position ◽  
Head Tracking ◽  
Complex Structures ◽  
Complex Objects ◽  
Multiple Images ◽  
Depth Images ◽  
Depth Cue

The paper presents a method for the simulation of motion parallax for monitor-based Augmented Reality (AR) applications. Motion parallax effects the relative movement between far and close objects: near objects appear moving faster than far objects do. This facilitates the perception of depth, distances, and the structure of geometrically complex objects. Today, industrial AR applications are equipped with monitor-based output devices, e.g., for design reviews. Thus this important depth cue is omitted because all objects appear as one even layer on screen. As a result, the assessment of complex structures becomes more difficult. The method presented in this paper utilizes depth images to create layered images: multiple images in which objects in a video image are split up with respect to their distance too a video camera. Using head tracking, the single layers are relatively moved with respect to the user’s head position. This simulates motion parallax. Virtual objects superimpose the final image to complete the AR scene. The method was prototypically realized, the results show its feasibility.

DEVELOPMENT OF PRINCIPLES FOR THE DESIGN OF COMPLEX TECHNICAL MEANS AND TECHNOLOGICAL PROCESSES OF CROP PRODUCTION

1970 ◽  
pp. 70-72
Author(s):  
D. N. Radnaev ◽  
Yu. А. Sergeev ◽  
А. А. Abiduev ◽  
S. V. Petunov
Keyword(s):  
Crop Production ◽  
Design Methodology ◽  
Systematic Approach ◽  
Optimal Solution ◽  
Agricultural Science ◽  
Complex Objects ◽  
Technological Processes ◽  
Methods Of Synthesis ◽  
Working Bodies ◽  
Projected Process

Currently, agricultural science and practice has a large amount of experimental data that need to be taken into account in the development of new technological processes and working bodies. Therefore, there is a need to design technical processes in order to identify their effectiveness. In this regard, the use of methods of synthesis of technological processes based on the characteristics of tillage, seeding and production system of the economy, in which it is necessary to implement the projected process. In the General statement of the problem, the design of technological processes is one of the complex problems with the following characteristic feature: lack of knowledge about the methods of designing technological processes, suitable for system - structural modeling and algorithmization of design processes. To overcome this incompleteness, a systematic approach is needed. The system approach proceeds from the fact that the specificity of complex objects and processes is not limited to the features of its constituent parts and elements, but lies in the nature of relationships and relationships between them. In this paper, the design methodology is based on the formulated fundamental assumptions and principles of the whole system of more specific statements, revealing the structure and content of design operations, the synthesis of the choice of solutions. The principles of technological compatibility and emergence suitable for system-structural analysis of complex technical means and technological processes, consisting of statements having a hierarchical structure, where the degree of detail of the goals from level to level increases, and the approval of the last level determines the direction of the search for the optimal solution to the problem.

Less is more: Simple stimuli provoke more variable search strategies.

2020 ◽  
Author(s):  
Anna Nowakowska ◽  
Alasdair D F Clarke ◽  
Jessica Christie ◽  
Josephine Reuther ◽  
Amelia R. Hunt
Keyword(s):  
Line Segment ◽  
Search Strategies ◽  
Complex Objects ◽  
Search Behaviour ◽  
Line Segments ◽  
Surface Level ◽  
Efficient Search ◽  
Less Is More ◽  
Dramatic Shift

We measured the efficiency of 30 participants as they searched through simple line segment stimuli and through a set of complex icons. We observed a dramatic shift from highly variable, and mostly inefficient, strategies with the line segments, to uniformly efficient search behaviour with the icons. These results demonstrate that changing what may initially appear to be irrelevant, surface-level details of the task can lead to large changes in measured behaviour, and that visual primitives are not always representative of more complex objects.

Hierarchical composition in complex object drawing

2019 ◽  
Author(s):  
Michiru Makuuchi
Keyword(s):  
Hierarchical Structure ◽  
Homo Sapiens ◽  
Hierarchical Structures ◽  
Target Object ◽  
Point Of View ◽  
Complex Object ◽  
Complex Objects ◽  
Cognitive Domains ◽  
Adult Participants ◽  
Symbolic Cognition

Symbolic behaviours such as language, music, drawing, dance, etc. are unique to humans and are found universally in every culture on earth1. These behaviours operate in different cognitive domains, but they are commonly characterised as linear sequences of symbols2,3. One of the most prominent features of language is hierarchical structure4, which is also found in music5,6 and mathematics7. Current research attempts to address whether hierarchical structure exists in drawing. When we draw complex objects, such as a face, we draw part by part in a hierarchical manner guided by visual semantic knowledge8. More specifically, we predicted how hierarchical structure emerges in drawing as follows. Although the drawing order of the constituent parts composing the target object is different amongst individuals, some parts will be drawn in succession consistently, thereby forming chunks. These chunks of parts would then be further integrated with other chunks into superordinate chunks, while showing differential affinity amongst chunks. The integration of chunks to an even higher chunk level repeats until finally reaching the full object. We analysed the order of drawing strokes of twenty-two complex objects by twenty-five young healthy adult participants with a cluster analysis9 and demonstrated reasonable hierarchical structures. The results suggest that drawing involves a linear production of symbols with a hierarchical structure. From an evolutionary point of view, we argue that ancient engravings and paintings manifest Homo sapiens’ capability for hierarchical symbolic cognition.

DETECTING MYCOBACTERIUM TUBERCULOSIS RAPIDLY AND MYCOBACTERIUM TUBERCULOSIS STRAINS WITHOUT IS6110 SEQUENCE BY PCR ASSAY

2012 ◽  
pp. 15-19
Author(s):  
Thi Chau Anh Nguyen ◽  
Hoang Bach Nguyen ◽  
Hai Duong Huynh ◽  
Nu Xuan Thanh Le ◽  
Xuan Cuong Le ◽  
...  
Keyword(s):  
Mycobacterium Tuberculosis ◽  
16S Rdna ◽  
False Negative ◽  
Clinical Samples ◽  
Tuberculosis Complex ◽  
Pcr Assay ◽  
Complex Objects ◽  
Method Performance ◽  
Gene Coding ◽  
16S Rdna Pcr

Background: The Nested IS6110 PCR is used for detecting tuberculosis, however IS6110 sequence is not present in the genome of all strains of M.tuberculosis, the result may be false negative. The gene coding 16S ribosome always contains a short sequence specific to M. tuberculosis complex. Objects: Performance of the 16S Real-time PCR to detect M. tuberculosis and combining to the nested IS6110 PCR to determine the rate of Mtb strains without IS6110 from clinical samples. Materials and method: Performance of 16S rDNA PCR by commercial kit of Viet A Inc. for all 480 samples, the samples which were positive with the 16S rDNA PCR were retested in IS6110 PCR assay by in-house kit. Results: The Realtime 16S rDNA PCR detected 258 cases (53.8%) of tuberculosis. There were 3 (1.2 %) M. tuberculosis strains which do not harbor IS6110 sequence in genome. Conclusion: The IS6110 nested PCR can be applied more widely than the 16S rDNA realtime PCR. In case of using IS6110 PCR assay, results may show a low proportion of false negative. Combining 16S rDNA PCR with the IS6110 based PCR allowed detection of deletion of IS6110 sequence in M. tuberculosis isolates.

Indian Sign Language Recognition on PYNQ Board

2020 ◽  
Vol 13 ◽  
Author(s):  
Sukhendra Singh ◽  
G. N. Rathna ◽  
Vivek Singhal
Keyword(s):  
Sign Language ◽  
Hand Gesture ◽  
Language Recognition ◽  
Sign Language Recognition ◽  
Hand Gestures ◽  
Depth Images ◽  
Kinect Camera ◽  
Impaired People ◽  
Web Camera ◽  
Indian Sign Language

Introduction: Sign language is the only way to communicate for speech-impaired people. But this sign language is not known to normal people so this is the cause of barrier in communicating. This is the problem faced by speech impaired people. In this paper, we have presented our solution which captured hand gestures with Kinect camera and classified the hand gesture into its correct symbol. Method: We used Kinect camera not the ordinary web camera because the ordinary camera does not capture its 3d orientation or depth of an image from camera however Kinect camera can capture 3d image and this will make classification more accurate. Result: Kinect camera will produce a different image for hand gestures for ‘2’ and ‘V’ and similarly for ‘1’ and ‘I’ however, normal web camera will not be able to distinguish between these two. We used hand gesture for Indian sign language and our dataset had 46339, RGB images and 46339 depth images. 80% of the total images were used for training and the remaining 20% for testing. In total 36 hand gestures were considered to capture alphabets and alphabets from A-Z and 10 for numeric, 26 for digits from 0-9 were considered to capture alphabets and Keywords. Conclusion: Along with real-time implementation, we have also shown the comparison of the performance of the various machine learning models in which we have found out the accuracy of CNN on depth- images has given the most accurate performance than other models. All these resulted were obtained on PYNQ Z2 board.

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