Methods and systems for monitoring a worker performing a crowdsourced task
The disclosed embodiments illustrate methods and systems for monitoring a worker performing a crowdsourced task being presented on a computing device. The method comprises performing at least one of a facial detection processing or an eye tracking processing, on a video stream captured by a camera of the computing device. An inattention instance of the worker is determined based on at least one of the facial detection processing or the eye tracking processing. Further, the inattention instance is communicated to a crowdsourcing platform, wherein the crowdsourced task is received from the crowdsourcing platform.
1. A method for monitoring a worker performing a crowdsourced task being presented on a computing device, the method comprising:
performing, by one or more processors in the computing device, at least one of a facial detection processing or an eye tracking processing, on a video stream captured by a camera of the computing device;
determining, by the one or more processors, an inattention instance of the worker, based on at least one of the facial detection processing or the eye tracking processing;
communicating, by the one or more processors, the determined inattention instance to a crowdsourcing platform to receive an instruction from the crowdsourcing platform for suspension of the crowdsourced task being presented on the computing device, wherein the crowdsourced task is received from the crowdsourcing platform; and
communicating, by the one or more processors, one or more responses to the crowdsourcing platform within a predetermined time interval for one or more sample tasks received from the crowdsourcing platform in an event of the suspension of the crowdsourced task, wherein a performance score of the worker is updated by the crowdsourcing platform based on a count of inattention instances and validation of the one or more responses provided by the worker.
2. The method of claim 1 , wherein the crowdsourced task is a video surveillance task.
3. The method of claim 1 , wherein the inattention instance corresponds to at least one of an absence of the face of the worker in the captured video stream, the worker looking away from a screen of the computing device for a predetermined time interval, or an eye-blinking rate of the worker not being within a predetermined range.
4. The method of claim 1 , wherein the computing device is one of a mobile phone, a smart-phone, a tablet computer, a Personal Digital Assistant (PDA), or any other mobile device, and wherein the camera is a front-facing camera of the computing device.
5. A system for monitoring a worker performing a crowdsourced task being presented on a computing device, the system comprising:
a camera; and
one or more processors in the computing device operable to:
perform at least one of a facial detection processing or an eye tracking processing on a video stream captured by the camera of the computing device;
determine an inattention instance of the worker, based on at least one of the facial detection processing or the eye tracking processing;
communicate the determined inattention instance to a crowdsourcing platform to receive an instruction from the crowdsourcing platform for suspension of the crowdsourced task being presented on the computing device, wherein the crowdsourced task is received from the crowdsourcing platform; and
communicate one or more responses to the crowdsourcing platform within a predetermined time interval for one or more sample tasks received from the crowdsourcing platform in an event of the suspension of the crowdsourced task, wherein a performance score of the worker is updated by the crowdsourcing platform based on a count of inattention instances and validation of the one or more responses provided by the worker with predetermined responses.
6. The system of claim 5 , wherein the crowdsourced task is a video surveillance task.
7. The system of claim 5 , wherein the inattention instance corresponds to at least one of an absence of the face of the worker in the captured video stream, the worker looking away from a screen of the computing device for a predetermined time interval, or an eye-blinking rate of the worker not being within a predetermined range.
8. The system of claim 5 , wherein the computing device is one of a mobile phone, a smart-phone, a tablet computer, a Personal Digital Assistant (PDA), or any other mobile device, and wherein the camera is a front-facing camera of the computing device.
9. A computer program product for use with a computing device, the computer program product comprising a non-transitory computer readable medium, the non-transitory computer readable medium stores a computer program code for monitoring a worker performing a crowdsourced task being presented on the computing device, the computer program code is executable by one or more processors in the computing device to:
perform at least one of a facial detection processing or an eye tracking processing, on a video stream captured by a camera of the computing device;
determine an inattention instance of the worker, based on at least one of the facial detection processing or the eye tracking processing, wherein the inattention instance corresponds to at least one of an absence of the face of the worker in the captured video stream, the worker looking away from a screen of the computing device for a predetermined time interval, or an eye-blinking rate of the worker not being within a predetermined range;
communicate the determined inattention instance to a crowdsourcing platform to receive an instruction from the crowdsourcing platform for suspension of the crowdsourced task being presented on the computing device, wherein the crowdsourced task is received from the crowdsourcing platform; and
communicate one or more responses to the crowdsourcing platform within a predetermined time interval for one or more sample tasks received from the crowdsourcing platform in an event of the suspension of the crowdsourced task, wherein a performance score of the worker is updated by the crowdsourcing platform based on a count of inattention instances and validation of the one or more responses provided by the worker with predetermined responses.
10. The computer program product of claim 9 , wherein the crowdsourced task is a video surveillance task.
11. The computer program product of claim 9 , wherein the computing device is one of a mobile phone, a smart-phone, a tablet computer, a Personal Digital Assistant (PDA), or any other mobile device, and wherein the camera is a front-facing camera of the computing device.
12. The method of claim 1 further comprising:
presenting, by the one or more processors, the one or more sample tasks based on an acceptance of the one or more sample tasks by the worker, wherein the one or more sample tasks are received after the suspension of the crowdsourced task being presented on the computing device; and
transmitting, by the one or more processors, one or more responses provided by the worker for the one or more sample tasks to the crowdsourcing platform.
13. The method of claim 1 further comprising receiving, by the one or more processors, a performance report associated with the worker, wherein the performance report of the worker includes at least one of the count of the inattention instances of the worker, a total time interval during which the worker was inattentive, the performance score of the worker, a number of the crowdsourced tasks performed by the worker, a total time spent by the worker on performing crowdsourced tasks, and a remuneration receivable by the worker.