Object proposal generation applying the distance dependent Chinese restaurant process
In application domains such as robotics, it is useful to represent the uncertainty related to the robot's belief about the state of its environment. Algorithms that only yield a single "best guess" as a result are not sufficient. In this paper, we propose object proposal generation based on non-parametric Bayesian inference that allows quantification of the likelihood of the proposals. We apply Markov chain Monte Carlo to draw samples of image segmentations via the distance dependent Chinese restaurant process. Our method achieves state-of-the-art performance on an indoor object discovery data set, while additionally providing a likelihood term for each proposal. We show that the likelihood term can effectively be used to rank proposals according to their quality.
Code (1)
Tasks
Bayesian InferenceObjectObject DiscoveryObject Proposal GenerationSimilar Papers 제목 키워드 기반
Complexity-Adaptive Distance Metric for Object Proposals Generation
Distance metric plays a key role in grouping superpixels to produce object proposals for object detection. We observe that existing distance metrics work primarily for low complexity cases. In this paper, we develop a no…
Objectobject-detectionObject DetectionSuperpixelsRadar-Camera Sensor Fusion for Joint Object Detection and Distance Estimation in Autonomous Vehicles
In this paper we present a novel radar-camera sensor fusion framework for accurate object detection and distance estimation in autonomous driving scenarios. The proposed architecture uses a middle-fusion approach to fuse…
2D Object DetectionAutonomous DrivingAutonomous VehiclesDistance regression+5Object Proposal Generation using Two-Stage Cascade SVMs
Object proposal algorithms have shown great promise as a first step for object recognition and detection. Good object proposal generation algorithms require high object recall rate as well as low computational cost, beca…
Computational EfficiencyObjectObject Proposal GenerationObject Recognition+2A New Target-specific Object Proposal Generation Method for Visual Tracking
Object proposal generation methods have been widely applied to many computer vision tasks. However, existing object proposal generation methods often suffer from the problems of motion blur, low contrast, deformation, et…
ObjectObject Proposal GenerationVisual TrackingDetecting Temporally Consistent Objects in Videos through Object Class Label Propagation
Object proposals for detecting moving or static video objects need to address issues such as speed, memory complexity and temporal consistency. We propose an efficient Video Object Proposal (VOP) generation method and sh…
ClusteringObjectobject-detectionObject Detection