Body condition scoring (BCS) is the most widely used method to assess changes in body fat reserve... more Body condition scoring (BCS) is the most widely used method to assess changes in body fat reserves, which reflects its high potential to be included in on-farm welfare assessment protocols. Currently used scoring systems in dairy goats require animal restraint for body palpation. In this study, the Animal Welfare Indicators project (AWIN) proposes to overcome this constraint by developing a scoring system based only on visual assessment. The AWIN visual body condition scoring system highlights representative animals from 3 categories: very thin, normal, and very fat, and was built from data sets with photographs of animals scored by a commonly used 6-point scoring system that requires palpation in 2 anatomical regions. Development of the AWIN scoring system required 3 steps: (1) identification and validation of a body region of interest; (2) sketching the region from photographs; and (3) creation of training material. The scoring system's reliability was statistically confirmed....
In this paper, we address the problem of recogniz-ing multiple known objects under partial views ... more In this paper, we address the problem of recogniz-ing multiple known objects under partial views and occlusion. We consider the situation in which the view of the camera can be controlled in the sense of an active perception planning problem. One common approach consists of formulating such active object recognition in terms of information theory, namely to select actions that maximize the expected value of the observation in terms of the recognition belief. In our work, instead we formulate the active perception planning as a Partially Observable Markov Decision Process (POMDP) with reward solely associated with minimization of the recognition time. The returned policy is the same as the one obtained using the information value. By recognizing observations as a time consuming process and imposing constrains on time, we minimize the number of observations and consequently maximize the value of each one for the recognition task. Separating the reward from the belief in the POMDP enab...
2014 IEEE International Conference on Robotics and Automation (ICRA), Jun 2014
We introduce the Partial View Heat Kernel (PVHK) descriptor, for the purpose of 3D object represe... more We introduce the Partial View Heat Kernel (PVHK) descriptor, for the purpose of 3D object representation and recognition from partial views, assumed to be partial object surfaces under self occlusion. PVHK describes partial views in a geometrically meaningful way, i.e., by establishing a unique relation between the shape of the view and the descriptor. PVHK is also stable with respect to sensor noise and therefore adequate for sensors, such as the current active 3D cameras. Furthermore, PVHK takes full advantage of the dual 3D/RGB nature of current sensors and seamlessly incorporates appearance information onto the 3D information. We formally define the PVHK descriptor, discuss related work, provide evidence of the PVHK properties and validate them in three purposefully diverse datasets, and demonstrate its potential for recognition tasks.
We contribute a novel algorithm for the digitation of complete 3D object models that requires lit... more We contribute a novel algorithm for the digitation of complete 3D object models that requires little preparation effort from the user. Notably, the presented algorithm, Joint Alignment and Stitching of Non-Overlapping Meshes (JASNOM), completes 3D object models by aligning and stitching two 3D meshes by the boundaries and does not require any previous registration between them. JASNOMonly requirement is the lack of overlap between meshes, which is simple to achieve in most man made object. JASNOM takes advantage that both meshes can only be connected by their boundary to reframe the alignment problem as a search of the best assignment between boundary vertices. To make the problem tractable, JASNOM reduces the search space considerably by imposing strong constraints on valid assignments that transform the original combinatorial problem into a discrete linear problem. By not requiring previous camera registration and by not depending on shape features, JASNOM contributions range from quick modeling of 3D objects to hole filling in meshes.
2014 2nd International Conference on 3D Vision, Dec 2014
The current paper addresses the problem of object identification from multiple 3D partial views, ... more The current paper addresses the problem of object identification from multiple 3D partial views, collected from different view angles, with the objective of disambiguating between similar objects. We assume a mobile robot equipped with a depth sensor that autonomously grasps an object from different positions, with no previous known pattern. The challenge is to efficiently combine the set of observations into a single classification. We approach the problem with a multiple-hypothesis filter that allows to combine information from a sequence of observations given the robot movement. We further innovate by off-line learning neighborhoods between possible hypothesis based on the similarity of observations. Such neighborhoods translate directly the ambiguity between objects, and allow to transfer the knowledge of one object to the other. In this paper we introduce our algorithm, Multiple Hypothesis for Object Class Disambiguation from Multiple Observations, and evaluate its accuracy and efficiency.
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012
In this video we briefly illustrate the progress and contributions made with our mobile, indoor, ... more In this video we briefly illustrate the progress and contributions made with our mobile, indoor, service robots CoBots (Collaborative Robots), since their creation in 2009. Many researchers, present authors included, aim for autonomous mobile robots that robustly perform service tasks for humans in our indoor environments. The efforts towards this goal have been numerous and successful, and we build upon them. However, there are clearly many research challenges remaining until we can experience intelligent mobile robots that are fully functional and capable in our human environments.
Although since the days of the Shakey robot, there have been a rich variety of mobile robots, we ... more Although since the days of the Shakey robot, there have been a rich variety of mobile robots, we realize that there were still no general autonomous, unsupervised mobile robots servicing users in our buildings. In this paper, we contribute the algorithms and results of our successful deployment of a service mobile robot agent, CoBot, in our multi-floor office environment. CoBot accepts requests from users, autonomously navigates between floors of the building, and asks for help when needed in a symbiotic relationship with the humans in its environment. We present the details of such challenging deployment, in particular the effective real-time depth-camera based localization and navigation algorithms, the symbiotic human-robot interaction approach, and the multitask dynamic planning and scheduling algorithm. We conclude with a comprehensive analysis of the extensive results of the last two weeks of daily CoBot runs for a total of more than 8.7 km, performing a large varied set of user requests. partment, Carnegie Mellon University, USA mmv, srosenth at cs.cmu.edu
Visual object detection in robot soccer is fundamental so the robots can act to accomplish their ... more Visual object detection in robot soccer is fundamental so the robots can act to accomplish their tasks. Current techniques rely on manually highly polished definitions of object models, that lead to accurate detection, but are quite often computationally inefficient. In this work, we contribute an efficient object detection through regression (ODR) method based on offline training. We build upon the observation that objects in robot soccer are of a well defined color and investigate an offline learning approach to model such objects. ODR consists of two main phases: (i) offline training, where the objects are automatically labeled offline by existing techniques, and (ii) online detection, where a given image is efficiently processed in real-time with the learned models. For each image, ODR determines whether the object is present and provides its position if so. We show comparing results with current techniques for precision and computational load.
In order to test the structural evolution changes of the standard solar model, we reconstruct a l... more In order to test the structural evolution changes of the standard solar model, we reconstruct a luminosity curve on a scale of a few millennia. This reconstruction is based on a previously reconstructed data series of the average behavior of the sunspot number. Then we study the model’s response to this luminosity curve for several evolution scenarios. The structural changes seem to be dominated by the dynamics of the upper layers of the star. Helioseismology analysis suggests that the external layers of the super-adiabatic region (on an extension of 0.2R⊙) could be responsible for these luminosity variations.
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Papers by Susana Brandao
effort from the user. Notably, the presented algorithm, Joint Alignment and Stitching of Non-Overlapping
Meshes (JASNOM), completes 3D object models by aligning and stitching two 3D meshes by the boundaries
and does not require any previous registration between them. JASNOMonly requirement is the lack of overlap
between meshes, which is simple to achieve in most man made object. JASNOM takes advantage that both
meshes can only be connected by their boundary to reframe the alignment problem as a search of the best
assignment between boundary vertices. To make the problem tractable, JASNOM reduces the search space
considerably by imposing strong constraints on valid assignments that transform the original combinatorial
problem into a discrete linear problem. By not requiring previous camera registration and by not depending
on shape features, JASNOM contributions range from quick modeling of 3D objects to hole filling in meshes.