Method for training a classifier, the method comprising: capturing sensor data of a scene at a first and a second sensor, respectively, at corresponding points in time, wherein said first sensor is an image sensor configured to deliver two dimensional images of said scene and wherein the second sensor is any sensor type from the group of visible light image sensor, infra-red light image sensor, radar sensor, LIDAR sensor, sonar sensor, and X-ray sensor, generating by the first sensor a first set of sensor data including data representing an object or an event in a monitored environment, generating by the second sensor a second set of sensor data representing a corresponding time period as a time period represented by the first set of sensor data, detecting at an object detector an object appearing in an image of the scene captured in said first set of sensor data, cropping at a cropping module from the first set of sensor data a subset of data representing the detected object, a cropping area thereof being determined by the position and size of the detected object, determining at said cropping module features of said cropping area, said features comprising a position of the detected object, an indication of the area occupied by the object, a width of the cropping area, a height of the cropping area and/or a direction of the cropping area, inputting to a tutor classifier said cropping area, generating a classification of the object or event in the tutor classifier, receiving the second set of sensor data at an apprentice classifier training process, translating at a crop translator said features of the cropping area into a corresponding position represented in the second set of sensor data, determining at a cropping module cropping parameters at least partially based on the translated features, wherein the second set of sensor data is then cropped using said cropping parameters, receiving the classification generated in the tutor classifier at the apprentice classifier training process, and training the apprentice classifier in the apprentice classifier training process using the cropped data of the second set of sensor data as input and using the classification received from the tutor classifier as a ground-truth for the classification of the second set of sensor data. capturing sensor data of a scene at a first and a second sensor, respectively, at corresponding points in time, wherein said first sensor is an image sensor configured to deliver two dimensional images of said scene and wherein the second sensor is any sensor type from the group of visible light image sensor, infra-red light image sensor, radar sensor, LIDAR sensor, sonar sensor, and X-ray sensor, generating by the first sensor a first set of sensor data including data representing an object or an event in a monitored environment, generating by the second sensor a second set of sensor data representing a corresponding time period as a time period represented by the first set of sensor data, detecting at an object detector an object appearing in an image of the scene captured in said first set of sensor data, cropping at a cropping module from the first set of sensor data a subset of data representing the detected object, a cropping area thereof being determined by the position and size of the detected object, determining at said cropping module features of said cropping area, said features comprising a position of the detected object, an indication of the area occupied by the object, a width of the cropping area, a height of the cropping area and/or a direction of the cropping area, inputting to a tutor classifier said cropping area, generating a classification of the object or event in the tutor classifier, receiving the second set of sensor data at an apprentice classifier training process, translating at a crop translator said features of the cropping area into a corresponding position represented in the second set of sensor data, determining at a cropping module cropping parameters at least partially based on the translated features, wherein the second set of sensor data is then cropped using said cropping parameters, receiving the classification generated in the tutor classifier at the apprentice classifier training process, and training the apprentice classifier in the apprentice classifier training process using the cropped data of the second set of sensor data as input and using the classification received from the tutor classifier as a ground-truth for the classification of the second set of sensor data.