A Mathematical Method for Computing the Contour Closure

2012 ◽  
Vol 457-458 ◽  
pp. 1486-1489
Author(s):  
Xiao Fang Shao ◽  
Ming Juan Cai
Keyword(s):  
Mathematical Method ◽  
Human Perception ◽  
Experimental Results ◽  
Virtual Line ◽  
Specific Instance

This paper puts forward a mathematical method for computing the closure extent of object contours—a specific instance of Gestalt law of closure. The method introduces the concept of virtual line to interpret the size of contour gaps vector points and measure the closure extent. Experimental results show that the computation results is consistent with the human perception interpretation in most cases.

A Computation Method for Symmetry

2012 ◽  
Vol 562-564 ◽  
pp. 1266-1271
Author(s):  
Wei Feng ◽  
Xiao Fang Shao ◽  
Ming Juan Cai ◽  
Bin Cao
Keyword(s):  
Mathematical Method ◽  
Symmetry Property ◽  
Human Perception ◽  
Experimental Results ◽  
Computation Method ◽  
Specific Instance

This paper puts forward a mathematical method to measure the symmetry property of two image elements—a specific instance of the Gestalt law of symmetry. The method makes an abstract of image elements by introducing vector points and experimental results show that the computation results is consistent with the human perception interpretation in most cases.

Computer Restoration of 2D Medical Diagnostic Signals with Noise Frequency Spectrum

1970 ◽  
Vol 111 (5) ◽  
pp. 133-136
Author(s):  
M. Nikolova ◽  
Tz. Dimitrova
Keyword(s):  
Mathematical Method ◽  
Frequency Spectrum ◽  
Frequency Band ◽  
Low Frequency ◽  
Experimental Results ◽  
Medical Diagnostic ◽  
Noise Frequency ◽  
Influence Of Noise

An application of mathematical method of Aisenberg for restoration of low frequency medical diagnostic signals after influence of noise is described in the paper. The restoration of frequency spectrum of medical diagnostic signals has been done after preliminary analyses of frequency spectrum of signals with noise and disposition of frequency band of noise in the frequency band of information signals. Some experimental results obtained on the base of application of Aisenberg's method for restoration of medical diagnostic signals are described in the paper. Ill. 9, bibl. 8 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.111.5.374

scholarly journals Generating Robust Audio Adversarial Examples with Temporal Dependency

2020 ◽  
Author(s):  
Hongting Zhang ◽  
Pan Zhou ◽  
Qiben Yan ◽  
Xiao-Yang Liu
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Defense Mechanisms ◽  
User Study ◽  
State Of The Art ◽  
Temporal Structure ◽  
Human Perception ◽  
Experimental Results ◽  
Low Intensity ◽  
Adversarial Examples

Audio adversarial examples, imperceptible to humans, have been constructed to attack automatic speech recognition (ASR) systems. However, the adversarial examples generated by existing approaches usually incorporate noticeable noises, especially during the periods of silences and pauses. Moreover, the added noises often break temporal dependency property of the original audio, which can be easily detected by state-of-the-art defense mechanisms. In this paper, we propose a new Iterative Proportional Clipping (IPC) algorithm that preserves temporal dependency in audios for generating more robust adversarial examples. We are motivated by an observation that the temporal dependency in audios imposes a significant effect on human perception. Following our observation, we leverage a proportional clipping strategy to reduce noise during the low-intensity periods. Experimental results and user study both suggest that the generated adversarial examples can significantly reduce human-perceptible noises and resist the defenses based on the temporal structure.

scholarly journals A Novel Key-Frame Extraction Approach for Both Video Summary and Video Index

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Shaoshuai Lei ◽  
Gang Xie ◽  
Gaowei Yan
Keyword(s):  
Human Perception ◽  
Extraction Methods ◽  
Experimental Results ◽  
Semantic Structure ◽  
New Approach ◽  
Key Frame Extraction ◽  
Key Frame ◽  
Video Summary ◽  
Key Frames ◽  
Svd Decomposition

Existing key-frame extraction methods are basically video summary oriented; yet the index task of key-frames is ignored. This paper presents a novel key-frame extraction approach which can be available for both video summary and video index. First a dynamic distance separability algorithm is advanced to divide a shot into subshots based on semantic structure, and then appropriate key-frames are extracted in each subshot by SVD decomposition. Finally, three evaluation indicators are proposed to evaluate the performance of the new approach. Experimental results show that the proposed approach achieves good semantic structure for semantics-based video index and meanwhile produces video summary consistent with human perception.

scholarly journals A Method for Recognizing and Separating Trademark Image Outer Frames

2002 ◽  
Vol 6 (3) ◽  
pp. 116-125
Author(s):  
Koji Abe ◽  
◽  
Haruhiko Kimura ◽  
Hideo Nagashima ◽  
Taki Kanda ◽  
...  
Keyword(s):  
Image Retrieval ◽  
Experimental Evaluation ◽  
Human Perception ◽  
Experimental Results ◽  
Content Based Image Retrieval ◽  
Registered Trademark ◽  
Outer Frame ◽  
Trademark Registration ◽  
Trademark Images

We present a method for recognizing the existence of outer frames in binary trademark images and segmenting a trademark that contains an outer frame into the frame and its inner figure, even if both touch. This focuses on the development of content-based image retrieval (CBIR) for trademark registration. Using our proposed method, CBIR systems examine the similarity between images using only main image components. This includes a study for describing image components. We detail criteria of trademark image outer frames and propose an algorithm for recognizing and segmenting outer frames based on the criteria. Experimental results using 1843 registered trademark images and experimental evaluation by 13 participants showed that 98.4% of recognitions agreed with human perception.

scholarly journals Pose and Illumination Invariance of Attribute Detectors in Person Re-identification

2018 ◽  
Vol 7 (4.11) ◽  
pp. 174
Author(s):  
Mohammadali Saghafi ◽  
Aini Hussain ◽  
Mohamad Hanif Md. Saad ◽  
Mohd Asyraf Zulkifley ◽  
Nooritawati Md Tahir ◽  
...  
Keyword(s):  
Video Surveillance ◽  
Negative Impact ◽  
Human Perception ◽  
Light Variation ◽  
Experimental Results ◽  
Visual Features ◽  
Illumination Invariance ◽  
Surveillance Applications ◽  
Quantitative Nature

The use of attributes in person re-identification and video surveillance applications has grabbed attentions of many researchers in recent times. Attributes are suitable tools for mid-level representation of a part or a region in an image as it is more similar to human perception as compared to the quantitative nature of the normal visual features description of those parts. Hence, in this paper, the preliminary experimental results to evaluate the robustness of attribute detectors against pose and light variations in contrast to the use of local appearance features is discussed. Results attained proven that the attribute-based detectors are capable to overcome the negative impact of pose and light variation towards person re-identification activities. In addition, the degree of importance of different attributes in re-identification is evaluated and compared with other previous works in this field.  

Evaluating In-Vehicle Sound and Vibration during Incursions on Sinusoidal Rumble Strips

2020 ◽  
pp. 036119812096794
Author(s):  
Dylan Horne ◽  
Hisham Jashami ◽  
Christopher M. Monsere ◽  
Sirisha Kothuri ◽  
David S. Hurwitz
Keyword(s):  
Haptic Feedback ◽  
Human Perception ◽  
Interior Noise ◽  
Experimental Results ◽  
Heavy Vehicle ◽  
Climate Control ◽  
Perception Threshold ◽  
Passenger Car ◽  
Vibration Sensors ◽  
Acceptable Range

Rumble strips (RS) are a countermeasure used to reduce roadway-departure crashes by providing audible and haptic alerts to the driver when a vehicle is departing the roadway. This study evaluated the feasibility of using sinusoidal RS as a substitute for more traditional rounded RS. A van, a passenger car, and a heavy vehicle were equipped with sound and vibration sensors to measure the interior noise and haptic feedback of each RS design. A set of typical conditions (with interior climate control fan and radio turned on) were also tested. Data from 75 RS strikes were analyzed. Experimental results demonstrated that the rounded RS doubled interior noise for the passenger car and van (11.3 dBA, 10.0 dBA) but the sinusoidal RS also generated a clearly noticeable interior alert for the passenger car and van (5.8 dBA, 4.6 dBA). The haptic alert provided an increase over the human perception threshold of vibration for all vehicles. The sinusoidal RS interior alert was detectable and within the acceptable range, but not clearly noticeable (5 dBA) when the climate control and radio were active. Alert levels for the rounded RS were >10 dBA, doubling the amount of interior noise for all ambient factor groups (11.2–14.4 dBA).

scholarly journals Multi-Instance Learning with Key Instance Shift

2017 ◽  
Author(s):  
Ya-Lin Zhang ◽  
Zhi-Hua Zhou
Keyword(s):  
Test Data ◽  
Real World ◽  
Test Phase ◽  
Experimental Results ◽  
Positive Instance ◽  
Class Model ◽  
Specific Instance ◽  
Importance Weights

Multi-instance learning (MIL) deals with the tasks where each example is represented by a bag of instances. A bag is positive if it contains at least one positive instance, and negative otherwise. The positive instances are also called key instances. Only bag labels are observed, whereas specific instance labels are not available in MIL. Previous studies typically assume that training and test data follow the same distribution, which may be violated in many real-world tasks. In this paper, we address the problem that the distribution of key instances varies between training and test phase. We refer to this problem as MIL with key instance shift and solve it by proposing an embedding based method MIKI. Specifically, to transform the bags into informative vectors, we propose a weighted multi-class model to select the instances with high positiveness as instance prototypes. Then we learn the importance weights for transformed bag vectors and incorporate original instance weights into them to narrow the gap between training/test distributions. Experimental results validate the effectiveness of our approach when key instance shift occurs.

scholarly journals Segmentation of color images by chromaticity features using self-organizing maps

2016 ◽  
Vol 36 (2) ◽  
pp. 78 ◽  
Author(s):  
Farid García-Lamont ◽  
Alma Delia Cuevas Rasgado ◽  
Yedid Erandini Niño Membrillo
Keyword(s):  
Image Segmentation ◽  
A Priori ◽  
Human Perception ◽  
Color Images ◽  
Experimental Results ◽  
A Priori Knowledge ◽  
Self Organizing Map ◽  
Uniform Illumination ◽  
Self Organizing Maps ◽  
Self Organizing

Usually, the segmentation of color images is performed using cluster-based methods and the RGB space to represent the colors. The drawback with these methods is the a priori knowledge of the number of groups, or colors, in the image; besides, the RGB space issensitive to the intensity of the colors. Humans can identify different sections within a scene by the chromaticity of its colors of, as this is the feature humans employ to tell them apart. In this paper, we propose to emulate the human perception of color by training a self-organizing map (SOM) with samples of chromaticity of different colors. The image to process is mapped to the HSV space because in this space the chromaticity is decoupled from the intensity, while in the RGB space this is not possible. Our proposal does not require knowing a priori the number of colors within a scene, and non-uniform illumination does not significantly affect the image segmentation. We present experimental results using some images from the Berkeley segmentation database by employing SOMs with different sizes, which are segmented successfully using only chromaticity features.

A Model of Mechanisms Mediating Spatial Pattern Perception

1992 ◽  
Vol 36 (18) ◽  
pp. 1430-1434
Author(s):  
Mark W. Cannon
Keyword(s):  
Spatial Pattern ◽  
Real World ◽  
Human Perception ◽  
Experimental Results ◽  
Pattern Perception ◽  
Image Sharpness ◽  
Spatial Filters ◽  
Apparent Contrast ◽  
Linear Transducer ◽  
Non Linear

A model consisting of multiple tuned and oriented spatial filters followed by non-linear transducer functions is described. The model was originally derived to account for human perception of contrast while viewing isolated stimuli. The model can also account for human estimates for the image sharpness of spatially filtered real world scenes. The model has several shortcomings uncovered by recent experimental results involving suppression of the apparent contrast of a foveally presented grating patch by a peripheral grating.

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