Perception & Action Lab
at Ulsan National Institue of Science & Technology
Imagine a frog that catches a fly using its tongue. To satisfy the needs for food, the frog’s visual system should have been developed to see and follow the trajectories of a fly efficiently. Then, what are the driving forces that make humans see and interact with the world the way we do? What are the computational principles that govern human perception and action? In everyday activities, why are some devices easier to interact with than others?
Within a static object envelope, a pattern motion changes direction at a continuous rate. The resulting static object is perceived to follow a circular object trajectory in visual periphery. Illusions provide clues to perceptual mechanisms. This illusion, which seems to demonstrate the failure of our visual system, is actually the result of optimal inference given noisy sensory signals (Kwon et al., 2015).
In Perception & Action Lab, we study 1) how the human perceptual system constructs representations of the world from incomplete and noisy sensory signals, 2) how our sensory-motor system coordinates to generate efficient responses, and 3) how we can apply those knowledge to improve the quality of life.
Current research areas include statistical learning in vision, motion perception, visuo-haptic cue integration, and vision of the aging population. To study these problems, we utilize various behavioral and physiological (through collaboration) measurement techniques and computational modeling. Especially, we are interested in building normative computational models that signify the (sub)optimality of human behaviors.
Liana N. Saftari (Grad student), email@example.com, Research interest: Aging and vision, motion perception and balancing.
Haerang Lee (Undergrad researcher), firstname.lastname@example.org, Research Interest: Statistical learning, Cognitive training.
Eunchong Kim (Undergrad researcher), email@example.com, Research Interest: Time perception, Human information processing.
Sungdong Jung (Undergrad researcher), firstname.lastname@example.org, Research interest: Cognitive biases, Perceptual learning for visual improvement.
Hanan Jamal Mohamed (Undergrad researcher), email@example.com, Research interest: Motion perception and Levy walk.
Byunghee Kwak (Undergrad researcher), firstname.lastname@example.org, Research interest: Evolution and perception.
Current and Former Collaborations
Zygmunt Pizlo: Purdue University, Psychological Sciences.
Howard Zelaznik: Purdue University, Health & Kinesiology.
George Chiu: Purdue University, Mechanical Engineering.
Jeffrey Shelton: Purdue University, Mechanical Engineering.
Eileen Kowler: Rutgers University, Psychology.
Chia-Chien Wu: Boston University, Center for Computational Neuroscience and Neural Technology.
David Knill: University of Rochester, Brain & Cognitive Sciences.
Duje Tadin: University of Rochester, Brain & Cognitive Sciences.
Ruyuan Zhang: University of Rochester, Brain & Cognitive Sciences.
Stanislaw Czyz: North-West University, South Africa, Physical Activity, Sport & Recreation.
Post Doctoral Researcher:
Applications are invited for a postdoctoral researcher position. This appointment is for 2 years, and available to start immediately. The monthly salary is 3,000,000 won. Applicants should hold or expect shortly to hold a PhD in psychology, human factors, cognitive science, or related fields, and have (or have a will to develop) strong computational modeling skills. Applicants are expected to have at least one first authored article in internationally respected peer reviewed journal.
Students having BA/BS/MS/MA in cognitive science, human factors engineering, neuroscience, computer science, psychology, math, or related fields are encouraged to contact Dr. Kwon for further information.
Peer reviewed journal
Indu, V., Knill, D.C., Ding, J, Kwon, O.-S., Bavelier, D., & Levi, D.M. (accepted) Recovering stereo vision by squashing bugs in a virtual reality environment. Phil. Trans. R. Soc. B
Czyż SH, Kwon O.-S., Marzec J, Styrkowiec P, Breslin G. (2015) Visual uncertainty influences the extent of an especial skill, Human Movement Science, 44, 143-149.
Zhang**, R., Kwon**, O.-S. & Tadin, D. (2013) Illusory motion of stationary stimuli in visual periphery: evidence for a strong centrifugal prior in in motion processing. Journal of Neuroscience, 33, 4415-4423. ** equally contributing authors.
Kwon, O.-S., & Knill, D.C. (2013) The brain uses adaptive internal models of scene statistics for sensorimotor estimation and planning. PNAS, 110(11), e1064-73.
Czyż S.H., Breslin G., Kwon, O.-S., Mazur, M., Kobiałka, K., Pizlo, Z. (2013) Especial skill effect across age and performance level: the nature and degree of generalization. Journal of Motor Behavior, 45(2), 139-152.
Kwon, O.-S., Zelaznik, H. N., Chiu, G. C., & Pizlo, Z. (2011) Human Motor Transfer Is Determined by the Scaling of Size and Accuracy of Movement. Journal of Motor Behavior, 43, 15-26.
Wu, C. C., Kwon, O.-S., & Kowler, E. (2010) Fitts’s Law and speed/accuracy trade-offs during the sequences of saccades: Implications for strategies of saccadic planning. Vision Research, 50, 2142–2157.
Kim, Y.S., Kim, S.H., Kwon, O.S., & Yeo, M.S. (2001). Psychological Structure of the Hue Modifying Adjectives in Korean. Journal of Korean Society of Color Studies,15(1), 21-29.
Lee, M.Y., Kim, Y.I., Kim, Y.S., Pak, H.S., Choi, Y.H., & Kwon, O.S. (2002). Korean color naming system for textile fashion industry. Journal of Korean Society of Color Studies, 16(2), 1-24.
Kwon, O.-S., & Pizlo, Z. (in revision) Early correction in human goal-directed movement.
Kwon, O.-S., & Knill, D.C. (in preparation) Sequential effects in velocity estimation of self-generated motion.
Kwon, O.-S., & Knill, D.C. (in preparation) Learning category contingent speed priors for object interception.
Kwon, O.S., Zhang, R., & Tadin, D. (in preparation). Temporal evolution of motion direction judgments.
Zhang, R., Kwon, O.S., & Tadin, D. (in preparation). Specificity and transfer in perceptual learning of motioin.
Shelton, J.N., Kwon, O.S. & Chiu, G. (2008). Rapid Computation of Time-Optimal, Open-Loop Forearm Movement, 17th International Federation of Automatic Control World Congress.
Kwon, O.S., Shelton, J.N. & Chiu, G. (2008). Single Feedback Model of Human Goal- directed Movement, ASME Dynamic Systems and Control Conference.
Conference abstracts (conference talks are marked with *)
*Kwon, O.S., Pizlo, Z., Zelaznik, H. N. & Chiu, G. (2005). Multi-resolution model of human motor control. The Annual Meeting of the Society for Mathematical Psychology.
Kwon, O.S., Pizlo, Z., Zelaznik, H. N. & Chiu, G. (2006). Multi-resolution model of human motor control. Vision Sciences Society Meeting.
*Kwon, O.S., & Shelton, J. N. (2007). Trajectories of Goal-directed Arm Movement. The Annual Meeting of the Society for Mathematical Psychology.
Kwon, O.S., Shelton, J. N. (2008). Intermittent feedback model of goal-directed forearm movement. Vision Sciences Society Meeting.
Kwon, O.S., Shelton, J. N., & Pizlo, Z. (2008). Early Feedback Model of human Goal- directed Movement. 49th Annual Meeting of the Psychonomic Society.
Kwon, O.S., & Knill, D (2010). Extrapolation of target movement is influenced by the preceding velocities rather than by the mean velocity. Vision Sciences Society Meeting.
Kwon, O.S., & Knill, D. (2011). Humans adaptively use temporal correlations in stimulus history to estimate velocity. Vision Sciences Society Meeting.
Kwon, O.S., & Knill, D. (2012). Temporal dependency in estimation of target velocity disappears in self-generated stimuli. Vision Sciences Society Meeting.
*Kwon, O.S., Tadin, D, & Knill, D. (2013). Bayesian observer model of
the motion induced position shift. Vision Sciences Society Meeting.
*Knill, D., & Kwon, O.S. (2013). Learning category contingent speed priors for object interception. Vision Sciences Society Meeting.
Kwon, O.S., Tadin, D, & Knill, D. (2014). An optimal object-tracking model provides a unifying account of motion and position perception COSYNE (Computational and Systems Neuroscience).
*Kwon, O.S., Tadin, D, & Knill, D. (2014). An optimal object-tracking model provides a unifying account of motion and position perception Modvis (Computational and Mathematical Models in Vision).
Kwon, O.S., Tadin, D, & Knill, D. (2014). Optimal tracking model accounts for perceptual conflict between motion and position in the curveball illusion. Vision Sciences Society Meeting.
*Kwon, O.S., Zhang, R., & Tadin, D. (2015). Temporal evolution of motion direction judgments. Vision Sciences Society Meeting.
Zhang, R., Kwon, O.S., &, Tadin, D. (2015). Specificity and transfer in perceptual learning of motion. Vision Sciences Society Meeting.
*Kwon, O.-S. (2015). Adaptation to Artificial and Natural Environment in Visual Motion Perception. International Congress of Physiological Anthropology.
A unifying model of visual position and motion perception. (April 17, 2015) Neuroscience retreat, University of Rochester.
Perception as statistical inference. (Oct 1, 2015) DHE seminar, UNIST.
시지각과 통계적 추론. (Oct 16, 2015) Dept. of Psychology Seminar, Pusan National University.