As discussed in a previous article, the U.S. Patent and Trademark Office recently published new subject matter eligibility examples directed to the abstract idea exception to patentability under 35 U.S.C. § 101. These "December 2016 examples" each involve a so-called business method. Business methods have, in general, been looked down upon by the courts and the USPTO for some time, but especially since the Alice Corp. Pty. Ltd. v. CLS Bank Int'l decision.
That case set forth a two-part test to determine whether claims are directed to patent-eligible subject matter. One must first determine whether the claim at hand is directed to a judicially-excluded law of nature, a natural phenomenon, or an abstract idea. If so, then one must further determine whether any element or combination of elements in the claim is sufficient to ensure that the claim amounts to significantly more than the judicial exclusion. But generic computer implementation of an otherwise abstract process does not qualify as "significantly more."
Alice was particularly impactful on business methods, because the Court held that financial and business transactions (the subject matter of many business method claims) are virtually per se abstract. As a consequence, most eligible business methods have to recite sufficient technical detail (usually computer-related software and hardware) in order to prevail in part two of the inquiry. In practice, this makes the distinction between business methods claims and software claims fuzzy at best.
Nonetheless, the USPTO has provided three examples of business methods that can be claimed in a fashion that is eligible. In last week's article, we discussed the first two (Examples 34 and 35), and here we will cover Example 36.
Example 36 is a hypothetical invention provided by the USPTO. Thus, it is not based on the facts of any particular case. This example is titled "Tracking Inventory," but is much more specific than that.
The claimed invention is directed to inventory management in a warehouse. In the prior art, tracking devices, such as RFID tags, may be attached to items stored therein. Using RFID equipment, one would be able to rapidly locate a particular item. However, this solution requires the overhead of attaching the RFID tags when storing items, and detaching these tags when removing the items from inventory. Other prior art methods used cameras to capture images of the items, more specifically, identification codes on the items. However, using a single camera for this purpose does not provide an accurate 3D location of the item when it is stored. Of course, items and their locations can be manually logged, but doing so requires even more overhead and is prone to data entry mistakes. As a result, known inventory management techniques have unacceptably high error rates.
In order to overcome these deficiencies, the invention uses a high-resolution camera array with overlapping views. Using this camera array, the contour and shape of stored items, as well as markings on these items can be recorded along with the 3D locations of the items. Recognition of objects uses a machine-learning-based pattern classifier, such as "a Gaussian mixture model, neural network, Bayes classifier or other known pattern classifier." According to this hypothetical, "computer vision technology has not been used in the manner disclosed by this inventor prior to the filing of the application."
The example includes three claims, which we will discuss in turn. Claim 1 recites:
1. A system for managing an inventory record comprising a memory and processor configured to perform the steps of:
(a) creating an inventory record for an item of inventory comprising acquired images of the item;
(b) adding classification data relating to the acquired images to the inventory record;
(c) adding location data relating to each acquired image to the inventory record; and
(d) updating the inventory record with a physical location of each item of inventory in the warehouse to thereby manage the items of inventory.
Conducting part one of the Alice analysis, the USPTO characterized the claim as being directed to an abstract idea due to its similarity to other claims deemed abstract. Particularly, the data collection, recognition, and storage steps are "similar to the data collection and management concepts" found abstract in previous cases. Additionally, unlike the eligible claims in Enfish, LLC v. Microsoft Corp., the claim's mere invocation of a memory and a processor does not provide a specific improvement to these computer components.
Turning to step two of Alice, the additional elements of "[a] memory for storing data and a processor for processing data are well‐understood, routine, conventional computer components, which in this claim are recited at a high level of generality and perform generic computer functions." Therefore, when viewed individually, these elements do not lend eligibility. Furthermore, viewing the elements as a combination only reflects "ordinary usage typically performed by a generic computer, as would be recognized by those of ordinary skill in the field of data processing." Therefore, claim 1 lacks an inventive concept and is ineligible under § 101.
The next exemplary claim recites:
2. A system for managing an inventory record by tracking the location of items of inventory in a warehouse:
a high‐resolution video camera array, each video camera positioned at pre‐determined locations with overlapping views, for acquiring at least one high‐resolution image sequence of each item of inventory;
a memory and processor configured to perform the steps of:
(a) creating an inventory record for an item of inventory comprising the acquired image sequence of the item from the video camera array;
(b) adding classification data relating to the acquired image sequence to the inventory record;
(c) adding location data relating to each acquired image to the inventory record, the location data providing a position of the item of inventory in the image sequence;
(d) reconstructing the 3‐D coordinates of an item of inventory using the location data from multiple overlapping images and prior knowledge of the location and field of view of the camera(s); and
(e) automatically updating the inventory record with the 3‐D coordinates of each item of inventory in the warehouse to thereby manage the items of inventory.
Beginning with part one of Alice, the USPTO concluded that this claim is also directed to an abstract idea, due to four of its steps being analogous to those of claim 1. Moving on to part two, the USPTO stated that the additional elements of "a high‐resolution video camera array at predetermined positions with overlapping views, memory and processor to (d) reconstruct the 3‐D coordinates of the item of inventory from multiple overlapping images obtained from the camera array and prior knowledge of the location and field of view of the camera(s)" were well-known and conventional. Since these components perform their typical functions, individually they do not contain an inventive concept.
But when viewed as an ordered combination, the story is different. Particularly, the recent Federal Circuit case of BASCOM Global Internet v. AT&T Mobility LLC, stands for the principle that a claim directed to an abstract idea, with additional elements that are individually generic and conventional, can be patent-eligible if the combination of these elements is non-conventional and non‐generic. In claim 2, "the use of [the] camera array provides the ability to track objects throughout the entire storage space rather than simply the view of a single camera and determine their 3‐D location without any of the manual steps that were required of previous methods." As noted above, such use is assumed to be non-conventional by the hypothetical. Moreover, the "claimed solution here is necessarily rooted in computer technology to address a problem specifically arising in the realm of computer vision systems," and the ordered combination of limitations yields a particular, useful application of the abstract idea. Therefore, the claim satisfies the second part of Alice, and is patent-eligible.
The final exemplary claim recites:
3. A system for managing inventory by tracking the location of items of inventory in a warehouse using image recognition, comprising:
a high‐resolution video camera array for acquiring at least one high resolution image sequence of each item;
a memory for storing the acquired image sequences, classification and location data relating to the acquired image sequences, and a recognition model representing contour information and character information of each item; and
a processor that is configured to manage inventory by performing, for each item, the steps of:
(a) creating an inventory record for the item comprising the acquired image sequence(s)of the item;
(b) extracting characteristics from the acquired image sequence(s) of an item to form feature vectors, the characteristics comprising contour information and character information that is stored in the inventory record as classification data relating to the acquired image sequence(s);
(c) recognizing and tracking the position of item in the image sequence as classification and location data by processing the feature vectors using the stored recognition model and adding the classification and location data to the inventory record;
(d) determining a physical location of the item in the warehouse using the location data relating to the item in the image sequence(s); and
(e) automatically updating the inventory record with the physical location of the item.
Applying step one of Alice, the USPTO concluded that this claim, like claims 1 and 2, is directed to an abstract idea because it entails "data collection and management techniques to practice the concept of inventory management." With regard to step two, the additional elements of "the camera array, memory and processor limitations do not amount to significantly more for the reasons discussed above for claims 1 and 2."
Viewing the elements as an ordered combination, however, results in the claim being determined to be eligible. The USPTO noted that:
[T]he camera array's acquisition of high resolution image sequences, and the processor's performance of step (b)'s extracting contour and character information from the images to create feature vectors, step (c)'s recognizing and tracking items of inventory using the feature vectors and a recognition model, and step (d)'s determining the physical location of the recognized items using the position of the item in the image sequence(s) is not well‐understood, routine, conventional activity in this field.
Accordingly, the claim recites features that improve over the inaccurate solutions of the past. Notably, this claim recites detail about how feature vectors are extracted from images, and then later used find the items. As a result, the claim is patent eligible.
Not unlike Example 35, which we discussed in the previous post, the eligible claims for Example 36 recite technical detail that goes beyond the high-level steps that are used in generic solutions to the problem. Chiefly, claim 2 recites how specific features of the camera array are used to carry out these steps, and claim 3 provides steps that are specific to a particular way of processing, storing, and retrieving representations of the images and the items' locations. On the other hand, claim 1 is ineligible because it recites a high-level process that could be carried out by generic hardware in virtually any fashion.
Rather than rejecting claim 1 as being indefinite or obvious, the USPTO is signaling that it will continue to use § 101 as a hammer to knock down overly-broad claims. Nonetheless, these examples provide illustrations of what type of technical detail and how much of it is needed to meet the requirements of the statute and Alice.