A VOTING SCHEME FOR PARTIAL OBJECT EXTRACTION UNDER CLUTTERED ENVIRONMENT

Shape extraction aims to detect and localize objects via the shape information. The paper presents a novel voting scheme that can extract partially occluded objects under cluttered environments using a single shape. It works by jointly figuring out the boundaries and resolving the geometric configurations. To model the missing part lead by occlusion, we discretize the shape template into a set of its subpart, named portions. Our representation of shape template is through a set of portion together with their interconnections. Instead of forming a fully connected network, our interconnections make the portions consistent with the chain along the boundary of shape template. Based on the representation, we formulate an auto-locked objective function that contains both the unary and pairwise terms and balances the effects of missing parts. Min-sum voting scheme with strategy driven by bottom–up information is then proposed to minimize the objective function. Conducted experiments show that proposed algorithm is promising for shape extraction with occlusion and noisy backgrounds and allows the non-rigid deformations.

Download Full-text

Robust autonomous flight in cluttered environment using a depth sensor

International Journal of Micro Air Vehicles ◽

10.1177/1756829320924528 ◽

2020 ◽

Vol 12 ◽

pp. 175682932092452

Author(s):

Liang Lu ◽

Alexander Yunda ◽

Adrian Carrio ◽

Pascual Campoy

Keyword(s):

High Speed ◽

Point Clouds ◽

Depth Sensor ◽

Cluttered Environments ◽

Industrial Plants ◽

Cluttered Environment ◽

Navigation Strategy ◽

Physical Sensors ◽

Aerial Vehicle ◽

Planning Objective

This paper presents a novel collision-free navigation system for the unmanned aerial vehicle based on point clouds that outperform compared to baseline methods, enabling high-speed flights in cluttered environments, such as forests or many indoor industrial plants. The algorithm takes the point cloud information from physical sensors (e.g. lidar, depth camera) and then converts it to an occupied map using Voxblox, which is then used by a rapid-exploring random tree to generate finite path candidates. A modified Covariant Hamiltonian Optimization for Motion Planning objective function is used to select the best candidate and update it. Finally, the best candidate trajectory is generated and sent to a Model Predictive Control controller. The proposed navigation strategy is evaluated in four different simulation environments; the results show that the proposed method has a better success rate and a shorter goal-reaching distance than the baseline method.

Download Full-text

Two-stage neural network for recognizing partially occluded objects

The Imaging Science Journal ◽

10.1179/136821905x50343 ◽

2005 ◽

Vol 53 (3) ◽

pp. 132-139 ◽

Cited By ~ 1

Author(s):

W-Y Wu ◽

S-Y Lin

Keyword(s):

Neural Network ◽

Two Stage ◽

Occluded Objects ◽

Partially Occluded

Download Full-text

Recognition of Partially Occluded Objects Using Perfect Hashing: An Efficient and Robust Approach

The 2nd Canadian Conference on Computer and Robot Vision (CRV'05) ◽

10.1109/crv.2005.66 ◽

2005 ◽

Cited By ~ 4

Author(s):

R. Dinesh ◽

D.S. Guru

Keyword(s):

Robust Approach ◽

Occluded Objects ◽

Partially Occluded ◽

Perfect Hashing

Download Full-text

Phenomena of Illusory Form: Can We Bridge the Gap between Levels of Explanation?

Perception ◽

10.1068/p241333 ◽

1995 ◽

Vol 24 (11) ◽

pp. 1333-1364 ◽

Cited By ~ 60

Author(s):

Lothar Spillmann ◽

Birgitta Dresp

Keyword(s):

Feature Detection ◽

Brain Research ◽

Form Perception ◽

Integrative Approach ◽

Levels Of Explanation ◽

Attentional Processes ◽

Occluded Objects ◽

Neurophysiological Mechanisms ◽

Partially Occluded ◽

Different Levels

The study of illusory brightness and contour phenomena has become an important tool in modern brain research. Gestalt, cognitive, neural, and computational approaches are reviewed and their explanatory powers are discussed in the light of empirical data. Two well-known phenomena of illusory form are dealt with, the Ehrenstein illusion and the Kanizsa triangle. It is argued that the gap between the different levels of explanation, bottom—up versus top—down, creates scientific barriers which have all too often engendered unnecessary debate about who is right and who is wrong. In this review of the literature we favour an integrative approach to the question of how illusory form is derived from stimulus configurations which provide the visual system with seemingly incomplete information. The processes that can explain the emergence of these phenomena range from local feature detection to global strategies of perceptual organisation. These processes may be similar to those that help us restore partially occluded objects in everyday vision. To understand better the Ehrenstein and Kanizsa illusions, it is proposed that different levels of analysis and explanation are not mutually exclusive, but complementary. Theories of illusory contour and form perception must, therefore, take into account the underlying neurophysiological mechanisms and their possible interactions with cognitive and attentional processes.

Download Full-text