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Journal articles on the topic 'Vision, Monocular'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Coday, Mary P., Michael A. Warner, Kurt V. Jahrling, and Peter A. D. Rubin. "Acquired Monocular Vision." Ophthalmic Plastic and Reconstructive Surgery 18, no. 1 (January 2002): 56–63. http://dx.doi.org/10.1097/00002341-200201000-00009.

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2

HOLM, EJLER. "NYSTAGMUS IN MONOCULAR VISION." Acta Ophthalmologica 5, no. 1-3 (May 27, 2009): 387–99. http://dx.doi.org/10.1111/j.1755-3768.1927.tb01020.x.

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3

Uozato, Hiroshi. "Binocular and Monocular Vision." JAPANESE ORTHOPTIC JOURNAL 35 (2006): 61–66. http://dx.doi.org/10.4263/jorthoptic.35.61.

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4

Kraut, Joel A., and Veronica Lopez-Fernandez. "Adaptation to Monocular Vision." International Ophthalmology Clinics 42, no. 3 (2002): 203–13. http://dx.doi.org/10.1097/00004397-200207000-00021.

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5

Dickmanns, Ernst Dieter, and Volker Graefe. "Dynamic monocular machine vision." Machine Vision and Applications 1, no. 4 (December 1988): 223–40. http://dx.doi.org/10.1007/bf01212361.

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6

Ihrig, Carolyn, and Daniel P. Schaefer. "Acquired Monocular Vision Rehabilitation program." Journal of Rehabilitation Research and Development 44, no. 4 (2007): 593. http://dx.doi.org/10.1682/jrrd.2006.06.0071.

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7

Erkelens, C. J., and R. van Ee. "Monocular symmetry in binocular vision." Journal of Vision 7, no. 4 (March 1, 2007): 5. http://dx.doi.org/10.1167/7.4.5.

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8

Guerrero, J. J., and C. Sagüés. "Navigation from Uncalibrated Monocular Vision." IFAC Proceedings Volumes 31, no. 3 (March 1998): 351–56. http://dx.doi.org/10.1016/s1474-6670(17)44110-3.

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9

Abel, Sharon M., and Christine Tikuisis. "Sound localization with monocular vision." Applied Acoustics 66, no. 8 (August 2005): 932–44. http://dx.doi.org/10.1016/j.apacoust.2004.11.011.

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10

Ramachandran, V. S., S. Cobb, and L. Levi. "Monocular double vision in strabismus." NeuroReport 5, no. 12 (July 1994): 1418. http://dx.doi.org/10.1097/00001756-199407000-00001.

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11

Ihrig, Carolyn. "Vision Rehabilitation Team Management of Acquired Monocular Vision." Optometry and Vision Science 90, no. 3 (March 2013): e89-e94. http://dx.doi.org/10.1097/opx.0b013e3182820d74.

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12

HAYHOE, MARY, BARBARA GILLAM, KELLY CHAJKA, and ELIA VECELLIO. "The role of binocular vision in walking." Visual Neuroscience 26, no. 1 (January 2009): 73–80. http://dx.doi.org/10.1017/s0952523808080838.

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AbstractDespite the extensive investigation of binocular and stereoscopic vision, relatively little is known about its importance in natural visually guided behavior. In this paper, we explored the role of binocular vision when walking over and around obstacles. We monitored eye position during the task as an indicator of the difference between monocular and binocular performances. We found that binocular vision clearly facilitates walking performance. Walkers were slowed by about 10% in monocular vision and raised their foot higher when stepping over obstacles. Although the location and sequence of the fixations did not change in monocular vision, the timing of the fixations relative to the actions was different. Subjects spent proportionately more time fixating the obstacles and fixated longer while guiding foot placement near an obstacle. The data are consistent with greater uncertainty in monocular vision, leading to a greater reliance on feedback in the control of the movements.

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Hartle, Brittney, Aishwarya Sudhama, Lesley M. Deas, Robert S. Allison, Elizabeth L. Irving, Mackenzie G. Glaholt, and Laurie M. Wilcox. "Contributions of Stereopsis and Aviation Experience to Simulated Rotary Wing Altitude Estimation." Human Factors: The Journal of the Human Factors and Ergonomics Society 62, no. 5 (June 18, 2019): 812–24. http://dx.doi.org/10.1177/0018720819853479.

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Objective We examined the contribution of binocular vision and experience to performance on a simulated helicopter flight task. Background Although there is a long history of research on the role of binocular vision and stereopsis in aviation, there is no consensus on its operational relevance. This work addresses this using a naturalistic task in a virtual environment. Method Four high-resolution stereoscopic terrain types were viewed monocularly and binocularly. In separate experiments, we evaluated performance of undergraduate students and military aircrew on a simulated low hover altitude judgment task. Observers were asked to judge the distance between a virtual helicopter skid and the ground plane. Results Our results show that for both groups, altitude judgments are more accurate in the binocular viewing condition than in the monocular condition. However, in the monocular condition, aircrew were more accurate than undergraduate observers in estimating height of the skid above the ground. Conclusion At simulated altitudes of 5 ft (1.5 m) or less, binocular vision provides a significant advantage for estimation of the depth separation between the landing skid and the ground, regardless of relevant operational experience. However, when binocular cues are unavailable aircrew outperform undergraduate observers, a result that likely reflects the impact of training on the ability to interpret monocular depth cues.

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14

Chen, Zhe, Zhen Zhang, Fengzhao Dai, Yang Bu, and Huibin Wang. "Monocular Vision-Based Underwater Object Detection." Sensors 17, no. 8 (August 3, 2017): 1784. http://dx.doi.org/10.3390/s17081784.

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15

Yin, Yingjie, De Xu, Zhengtao Zhang, Xingang Wang, and Wentai Qu. "Plane measurement based on monocular vision." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 27, no. 4 (February 27, 2014): 347–52. http://dx.doi.org/10.3724/sp.j.1187.2013.00347.

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16

Lane, David, Kaila Pomeranz, Shannon Findlay, and Daniel Miller. "Monocular Vision Loss: A Rare Cause." Clinical Practice and Cases in Emergency Medicine 3, no. 4 (August 6, 2019): 436–37. http://dx.doi.org/10.5811/cpcem.2019.6.43224.

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A 62-year-old woman with a history of metastatic breast cancer and known meningioma presented with unilateral vision loss associated with anisocoria and an afferent pupillary defect. On magnetic resonance imaging we found the cause to be optic nerve compression by a right frontal meningioma. Monocular vision-loss etiologies are anatomically localized to structures anterior to the optic chiasm. This case serves as a reminder that cerebral structures in this location must not be forgotten in the differential.

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17

Haugaløkken, Bent Oddvar Arnesen, Martin Breivik Skaldebø, and Ingrid Schjølberg. "Monocular vision-based gripping of objects." Robotics and Autonomous Systems 131 (September 2020): 103589. http://dx.doi.org/10.1016/j.robot.2020.103589.

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18

Puech, William, Jean-Marc Chassery, and Ioannis Pitas. "Cylindrical surface localization in monocular vision." Pattern Recognition Letters 18, no. 8 (August 1997): 711–22. http://dx.doi.org/10.1016/s0167-8655(97)00077-9.

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19

Bouffard, Marc A., Wayne T. Cornblath, Joseph F. Rizzo, Michael S. Lee, Lindsey B. DeLott, Eric R. Eggenberger, and Nurhan Torun. "Transient Monocular Vision Loss on Awakening." Journal of Neuro-Ophthalmology 37, no. 2 (June 2017): 122–25. http://dx.doi.org/10.1097/wno.0000000000000451.

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20

Buys, Nicholas, and Jorge Lopez. "Experience of Monocular Vision in Australia." Journal of Visual Impairment & Blindness 98, no. 9 (September 2004): 519–33. http://dx.doi.org/10.1177/0145482x0409800904.

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21

Trego, Melissa E., and Jean Marie Pagani. "Three presentations of monocular vision loss." Optometry - Journal of the American Optometric Association 77, no. 2 (February 2006): 82–87. http://dx.doi.org/10.1016/j.optm.2005.12.003.

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22

Day, SH. "Vision development in the monocular individual." American Journal of Ophthalmology 121, no. 1 (January 1996): 113–14. http://dx.doi.org/10.1016/s0002-9394(14)70569-0.

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23

Park, Se-Hyun, Ji-Hye Hwang, Jin-Sun Ju, Eun-Jeong Ko, Juang-Tak Ryu, and Eun-Yi Kim. "VFH-based Navigation using Monocular Vision." Journal of the Korea Industrial Information Systems Research 16, no. 2 (June 30, 2011): 65–72. http://dx.doi.org/10.9723/jksiis.2011.16.2.065.

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24

Dickmanns, Ernst Dieter, and Volker Graefe. "Applications of dynamic monocular machine vision." Machine Vision and Applications 1, no. 4 (December 1988): 241–61. http://dx.doi.org/10.1007/bf01212362.

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25

Timney, Brian. "Effects of brief monocular deprivation on binocular depth perception in the cat: A sensitive period for the loss of stereopsis." Visual Neuroscience 5, no. 3 (September 1990): 273–80. http://dx.doi.org/10.1017/s0952523800000341.

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AbstractThe period of susceptibility for binocular depth vision was studied in kittens by subjecting them to periods of monocular deprivation beginning at different ages. In an initial study, we found that normally reared kittens can learn a depth-discrimination task much more rapidly when tested binocularly than monocularly, even when testing is begun as early at 30 d. In subsequent experiments, kittens were monocularly deprived by eyelid suture, following which their monocular and binocular depth thresholds were measured using the jumping-stand procedure. We obtained the following results: (1) When monocular deprivation is applied before the time of natural eye opening but is discontinued by no later than 30 d, there is very Little effect on binocular depth thresholds. (2) When deprivation is begun at 90 d, binocular depth thresholds are unaffected. (3) When deprivation is begun between these two ages, the magnitude of the deficit varies with the period of deprivation and the age at which it begins. (4) By imposing brief (5 or 10 d) periods of deprivation, beginning at different ages, we were able to demonstrate that the peak of the sensitive period is between the ages of 35 and 45 d, with a fairly rapid decline in susceptibility outside those age limits. (5) Even with as little as 5 d of deprivation, substantial permanent deficits in binocular depth vision can be induced.

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26

Ninio, J. "Curvature Biases in Stereoscopic Vision." Perception 26, no. 1_suppl (August 1997): 287. http://dx.doi.org/10.1068/v970154.

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The reliability of in-depth curvature judgements for linear elements was studied with stereograms that contained two linear targets and a background representing a hemisphere. The targets were arcs facing to the left or to the right, like parentheses. Some formed binocular pairs with (type 1) or without (type 2) in-depth curvature. The others were monocular (type 3). The hemisphere in the background was generated by a random curve (Ninio, 1981 Perception10 403 – 410); it was either concave (hollow) or convex. The arcs had their binocular centre in the plane of the centre of the hemisphere. Each stereogram contained a type 1, and either a type 2 or a type 3 target. Subjects had to judge the hemisphere curvature, then the in-depth curvature of the targets in 32 different stereograms covering all curvature combinations. There were about 15% errors on type 1 targets, and 80% of these occurred when both the hemisphere and the target were convex, the target being perceived as concave, by transparency through the hemisphere. There were also about 15% errors on type 2 targets, but spread among all situations, the trend being to perceive them as slightly concave. The monocular stimuli (type 3) were judged to be frontoparallel in 70% of the cases. Otherwise, there was no directional bias except for monocular arcs on the nasal side, in conjunction with a concave background. Then, the perceived in-depth curvature was in the ‘generic’ direction predicted by associating the monocular arc in one image with a straight vertical segment in the other image.

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27

Wang, Hongxia, Xue-Xue Kang, and Yang Yu. "Nighttime Pedestrian Ranging Algorithm Based on Monocular Vision." Cybernetics and Information Technologies 16, no. 5 (October 1, 2016): 156–67. http://dx.doi.org/10.1515/cait-2016-0062.

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Abstract Since the traditional computer vision ranging algorithm is imperfect in pertinence and precision, night time monocular vision pedestrian ranging method is proposed for vehicular infrared night vision goggles. Firstly, the method calibrated the internal and external parameters of infrared night-vision goggles, then, it corrected distortion of collected Vehicular Infrared Night Vision Image, and finally it ranged objective pedestrians by using night time monocular vision pedestrian ranging algorithm. The experimental results show that this method has the characteristics of pertinence, high precision and good real-time, and has good practicability.

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28

Zhang, Zheng, Xiao Wei Liu, and Guang You Yang. "Research of Intelligent Localization of Target for Manipulator Based on the Monocular Vision." Applied Mechanics and Materials 246-247 (December 2012): 22–27. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.22.

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A kind of calculation model of 3D space transformation is introduced, which is applicable to the monocular vision of robot manipulator, and the three-dimensional space plane mapping problem of image plane to the actual horizontal plane of monocular vision has been solved. It transforms the imaging coordinate system of target in monocular vision into the world coordinate system of the manipulator, so as to calculate the relative position of targets and the manipulator. The algorithm has better accuracy and reliability, which is proved by contrasting and testing the calculation result of object coordinate system transformed to the actual position coordinates to the sampling points in embedded platform.

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29

Liu, Dongbo. "HUMAN DETECTION AND MOTION RECOVERY BASED ON MONOCULAR VISION." Revista Brasileira de Medicina do Esporte 27, no. 4 (August 2021): 419–24. http://dx.doi.org/10.1590/1517-8692202127042021_0113.

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ABSTRACT Objective: Provides interactive games and human animation real motion data and technical options. Therefore, how to complete the position, attitude detection, and motion recovery under monocular vision has become an important research direction. Methods: This paper improves the part-based human detection algorithm and uses the AdaBoost multi-instance learning algorithm to train the part detector. Results: The results show that obtaining blood pressure waveform based on monocular vision pulse wave is feasible and has generalization. Conclusions: The results show the feasibility and accuracy of the gait motion detection, motion recovery and analysis system for human lower limbs based on monocular vision. Level of evidence II; Therapeutic studies - investigation of treatment results.

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30

Urzua, Sarquis, Rodrigo Munguía, and Antoni Grau. "Vision-based SLAM system for MAVs in GPS-denied environments." International Journal of Micro Air Vehicles 9, no. 4 (June 6, 2017): 283–96. http://dx.doi.org/10.1177/1756829317705325.

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Using a camera, a micro aerial vehicle (MAV) can perform visual-based navigation in periods or circumstances when GPS is not available, or when it is partially available. In this context, the monocular simultaneous localization and mapping (SLAM) methods represent an excellent alternative, due to several limitations regarding to the design of the platform, mobility and payload capacity that impose considerable restrictions on the available computational and sensing resources of the MAV. However, the use of monocular vision introduces some technical difficulties as the impossibility of directly recovering the metric scale of the world. In this work, a novel monocular SLAM system with application to MAVs is proposed. The sensory input is taken from a monocular downward facing camera, an ultrasonic range finder and a barometer. The proposed method is based on the theoretical findings obtained from an observability analysis. Experimental results with real data confirm those theoretical findings and show that the proposed method is capable of providing good results with low-cost hardware.

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31

Alemu, Haile W., and Preetam Kumar. "Monocular Diplopia: An Optical Correction Modality." Case Reports in Ophthalmology 12, no. 2 (June 11, 2021): 501–6. http://dx.doi.org/10.1159/000513215.

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Post-surgical or traumatic corectopia is among the rare causes of monocular diplopia. A 26-years-old student presented to the Institute with a complaint of monocular double vision in the left eye. He had a penetrating ocular injury in the left eye and subsequently, undergone for multiple ocular surgeries. Following the final intraocular lens implantation, he experienced a monocular double vision in his left eye. Upon contact lens clinic presentation, visual acuities were 20/20 in the right and 20/320 in the left eye (improved to 20/25 with pinhole). Slit-lamp examination on the left eye revealed scarring in the superior nasal quadrant of the cornea, irregular mid-dilated pupil with exposed aphakic and pseudophakic portions. A range of different optical management options were implemented to eliminate monocular diplopia and to correct refractive error. Finally, a combination of prosthetic soft contact lens and spectacle correction was able to remove diplopia and provide binocular single vision.

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32

S, Alex David, K. Antony Kumar, and S. Ravi Kumar. "Vision-based Vehicle Detection Survey." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 1 (March 29, 2016): 31. http://dx.doi.org/10.3991/ijes.v4i1.5590.

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Nowadays thousands of drivers and passengers were losing their lives every year on road accident, due to deadly crashes between more than one vehicle. There are number of many research focuses were dedicated to the development of intellectual driver assistance systems and autonomous vehicles over the past decade, which reduces the danger by monitoring the on-road environment. In particular, researchers attracted towards the on-road detection of vehicles in recent years. Different parameters have been analyzed in this paper which includes camera placement and the various applications of monocular vehicle detection, common features and common classification methods, motion- based approaches and nighttime vehicle detection and monocular pose estimation. Previous works on the vehicle detection listed based on camera poisons, feature based detection and motion based detection works and night time detection.

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33

Jin, Hong Jiao, Shen Lin, and Shi Guang Luo. "An Road Obstacle Detection Method Based on Monocular Measurement." Applied Mechanics and Materials 55-57 (May 2011): 539–44. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.539.

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Obstacle detection in the intelligent vehicle vision navigation system occupies a very important role. The studies for the obstacles detecting, especially Monocular Measurement from the computer vision, simplifying monocular vision system to camera projection model. Getting the conversion relation between image coordinate and the world coordinate system through the geometry derivation to establish the measurement model and achieve the obstacle measurement. The experiment proved that the error of this measurement model selected is within the acceptable range.

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34

Cheda, Diego. "Monocular Depth Cues in Computer Vision Applications." ELCVIA Electronic Letters on Computer Vision and Image Analysis 13, no. 2 (June 7, 2014): 65. http://dx.doi.org/10.5565/rev/elcvia.620.

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35

Werneck, Nicolau Leal, and Anna Helena Reali Costa. "Mapping with Monocular Vision in Two Dimensions." International Journal of Natural Computing Research 1, no. 4 (October 2010): 56–65. http://dx.doi.org/10.4018/jncr.2010100106.

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This article presents the problem of building bi-dimensional maps of environments when the sensor available is a camera used to detect edges crossing a single line of pixels and motion is restricted to a straight line along the optical axis. The position over time must be provided or assumed. Mapping algorithms for these conditions can be built with the landmark parameters estimated from sets of matched detection from multiple images. This article shows how maps that are correctly up to scale can be built without knowledge of the camera intrinsic parameters or speed during uniform motion, and how performing an inverse parameterization of the image coordinates turns the mapping problem into the fitting of line segments to a group of points. The resulting technique is a simplified form of visual SLAM that can be better suited for applications such as obstacle detection in mobile robots.

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36

Richard, Bruno, Eva Chadnova, and Daniel H. Baker. "Binocular vision adaptively suppresses delayed monocular signals." NeuroImage 172 (May 2018): 753–65. http://dx.doi.org/10.1016/j.neuroimage.2018.02.021.

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37

Adrian, Julien, Johan Le Brun, Neil R. Miller, José-Alain Sahel, Gérard Saillant, and Bahram Bodaghi. "Implications of monocular vision for racing drivers." PLOS ONE 14, no. 12 (December 16, 2019): e0226308. http://dx.doi.org/10.1371/journal.pone.0226308.

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38

Kiuchi, Yuji. "About the perspective effect by monocular vision." Journal of the Institute of Television Engineers of Japan 43, no. 2 (1989): 187–88. http://dx.doi.org/10.3169/itej1978.43.187.

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39

Li, Weimin, and Yan Li. "Portable monocular light pen vision measurement system." Journal of the Optical Society of America A 32, no. 2 (January 13, 2015): 238. http://dx.doi.org/10.1364/josaa.32.000238.

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40

Theodoracatos, Vassilios E. "Occlusion-free monocular three-dimensional vision system." Optical Engineering 33, no. 10 (October 1, 1994): 3476. http://dx.doi.org/10.1117/12.179394.

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41

Benninger, Felix, and Israel Steiner. "Surprising cause of transient monocular vision loss." Practical Neurology 14, no. 6 (September 12, 2014): 448. http://dx.doi.org/10.1136/practneurol-2014-000945.

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42

Jiafa, Mao, Huang Wei, and Sheng Weiguo. "Target distance measurement method using monocular vision." IET Image Processing 14, no. 13 (November 1, 2020): 3181–87. http://dx.doi.org/10.1049/iet-ipr.2019.1293.

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43

Yi, Yingmin, and Ding Liu. "Simultaneous Localization and Mapping Using Monocular Vision." Journal of Nanoelectronics and Optoelectronics 7, no. 2 (March 1, 2012): 162–66. http://dx.doi.org/10.1166/jno.2012.1230.

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44

Wang, Ching-Cheng. "Monocular pose acquisition for machine vision applications." Computers & Industrial Engineering 21, no. 1-4 (January 1991): 379–83. http://dx.doi.org/10.1016/0360-8352(91)90121-l.

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45

Isotalo, Elina, Zoi Kapoula, Pierre-Henri Feret, Karine Gauchon, Françoise Zamfirescu, and Pierre-Marie Gagey. "Monocular versus binocular vision in postural control." Auris Nasus Larynx 31, no. 1 (March 2004): 11–17. http://dx.doi.org/10.1016/j.anl.2003.10.001.

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46

Lemaire, Thomas, Cyrille Berger, Il-Kyun Jung, and Simon Lacroix. "Vision-Based SLAM: Stereo and Monocular Approaches." International Journal of Computer Vision 74, no. 3 (February 9, 2007): 343–64. http://dx.doi.org/10.1007/s11263-007-0042-3.

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47

Çelik, Koray, and Arun K. Somani. "Monocular Vision SLAM for Indoor Aerial Vehicles." Journal of Electrical and Computer Engineering 2013 (2013): 1–15. http://dx.doi.org/10.1155/2013/374165.

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This paper presents a novel indoor navigation and ranging strategy via monocular camera. By exploiting the architectural orthogonality of the indoor environments, we introduce a new method to estimate range and vehicle states from a monocular camera for vision-based SLAM. The navigation strategy assumes an indoor or indoor-like manmade environment whose layout is previously unknown, GPS-denied, representable via energy based feature points, and straight architectural lines. We experimentally validate the proposed algorithms on a fully self-contained microaerial vehicle (MAV) with sophisticated on-board image processing and SLAM capabilities. Building and enabling such a small aerial vehicle to fly in tight corridors is a significant technological challenge, especially in the absence of GPS signals and with limited sensing options. Experimental results show that the system is only limited by the capabilities of the camera and environmental entropy.

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48

Rong, Yicheng, Zhiyong Zhang, Changzhen Qiu, and Zezheng Ye. "UAV ranging method based on monocular vision." Journal of Physics: Conference Series 1873, no. 1 (April 1, 2021): 012041. http://dx.doi.org/10.1088/1742-6596/1873/1/012041.

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49

Wang, Xu Feng, Xin Min Dong, Xing Wei Kong, and Jian Hui Zhi. "Vision Based Measurement of Refueling Drogue for Autonomous Aerial Refueling." Applied Mechanics and Materials 590 (June 2014): 618–22. http://dx.doi.org/10.4028/www.scientific.net/amm.590.618.

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Autonomous aerial refueling (AAR) can improve the long-distance and rapid strike capacities of an unmanned aerial vehicle (UAV) significantly by extending its range as well as loiter time. This paper has mainly studied on the measurement of refueling drogue during the docking phase of the probe-drogue UAV-AAR. Firstly, the monocular vision based drogue detection and recognition method is presented. Secondly, the measuring method of relative position between the drogue and UAV based on the model of camera calibration is researched. Finally, the semi-physical experimental system of drogue spacial location for UAV-AAR during short-range docking phase is constructed. The drogue measuring experiment based on monocular vision is implemented, and the performance of the monocular vision method for drogue measurement and the validity of the experimental scheme are verified.

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50

YI, Ying Min, and Yu Hui. "Simultaneous Localization and Mapping with Identification of Landmarks Based on Monocular Vision." Advanced Materials Research 366 (October 2011): 90–94. http://dx.doi.org/10.4028/www.scientific.net/amr.366.90.

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How to identify objects is a hot issue of robot simultaneous localization and mapping (SLAM) with monocular vision. In this paper, an algorithm of wheeled robot’s simultaneous localization and mapping with identification of landmarks based on monocular vision is proposed. In observation steps, identifying landmarks and locating position are performed by image processing and analyzing, which converts vision image projection of wheeled robots and geometrical relations of spatial objects into calculating robots’ relative landmarks distance and angle. The integral algorithm procedure follows the recursive order of prediction, observation, data association, update, mapping to have simultaneous localization and map building. Compared with Active Vision algorithm, Three dimensional vision and stereo vision algorithm, the proposed algorithm is able to identify environmental objects and conduct smooth movement as well.

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